Create app.py

app.py

@@ -0,0 +1,38 @@
+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+model_en_ur_name = "Helsinki-NLP/opus-mt-en-ur"
+model_ur_en_name = "Helsinki-NLP/opus-mt-ur-en"
+
+tokenizer_en_ur = MarianTokenizer.from_pretrained(model_en_ur_name)
+model_en_ur = MarianMTModel.from_pretrained(model_en_ur_name)
+
+tokenizer_ur_en = MarianTokenizer.from_pretrained(model_ur_en_name)
+model_ur_en = MarianMTModel.from_pretrained(model_ur_en_name)
+
+def translate_text(text, direction):
+    if not text.strip():
+        return "⚠️ Please enter some text."
+
+    if direction == "English → Urdu":
+        inputs = tokenizer_en_ur(text, return_tensors="pt", padding=True, truncation=True)
+        translated = model_en_ur.generate(**inputs)
+        return tokenizer_en_ur.decode(translated[0], skip_special_tokens=True)
+
+    else:
+        inputs = tokenizer_ur_en(text, return_tensors="pt", padding=True, truncation=True)
+        translated = model_ur_en.generate(**inputs)
+        return tokenizer_ur_en.decode(translated[0], skip_special_tokens=True)
+
+with gr.Blocks() as app:
+    gr.Markdown("# 🌐 English ↔ Urdu Translator")
+    gr.Markdown("Built with Hugging Face + Gradio")
+
+    text_input = gr.Textbox(lines=4, label="Input Text")
+    direction = gr.Radio(["English → Urdu", "Urdu → English"], value="English → Urdu")
+    output = gr.Textbox(label="Output")
+
+    btn = gr.Button("Translate")
+    btn.click(translate_text, [text_input, direction], output)
+
+app.launch()