# ==============================
# 🟢 Step 2: Import Required Packages
# ==============================
from transformers import MarianMTModel, MarianTokenizer
import gradio as gr

# ==============================
# 🟢 Step 3: Load Translation Model
# ==============================
model_name = "Helsinki-NLP/opus-mt-en-ur"  # English → Urdu model
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)

# ==============================
# 🟢 Step 4: Define 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 = model.generate(**inputs, max_length=100)
    urdu_text = tokenizer.decode(translated[0], skip_special_tokens=True)
    return urdu_text

# ==============================
# 🟢 Step 5: Create Gradio Interface
# ==============================
interface = gr.Interface(
    fn=translate_to_urdu,
    inputs=gr.Textbox(lines=3, placeholder="Enter English text here..."),
    outputs="text",
    title="🌍 English to Urdu Translator",
    description="Translate English sentences into Urdu using a pretrained Hugging Face model."
)

# ==============================
# 🟢 Step 6: Launch App
# ==============================
interface.launch(share=True)