Create app.py

app.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+# Define translation models
+models = {
+    "English to Urdu": "Helsinki-NLP/opus-mt-en-ur",
+    "Urdu to English": "Helsinki-NLP/opus-mt-ur-en"
+}
+
+# Load models
+loaded_models = {}
+for direction, model_name in models.items():
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    model = MarianMTModel.from_pretrained(model_name)
+    loaded_models[direction] = (tokenizer, model)
+
+# Translation function
+def translate(text, direction):
+    tokenizer, model = loaded_models[direction]
+    inputs = tokenizer(text, return_tensors="pt", padding=True)
+    translated = model.generate(**inputs)
+    output = tokenizer.decode(translated[0], skip_special_tokens=True)
+    return output
+
+# Gradio interface
+iface = gr.Interface(
+    fn=translate,
+    inputs=[
+        gr.Textbox(label="Enter Text"),
+        gr.Radio(["English to Urdu", "Urdu to English"], label="Translation Direction")
+    ],
+    outputs=gr.Textbox(label="Translated Text"),
+    title="English ↔ Urdu Translator 🌐",
+    description="Translate between English and Urdu using Hugging Face models."
+)
+
+iface.launch()