Update app.py

app.py

@@ -7,67 +7,51 @@ import gradio as gr
 # ---- Load model and tokenizer ----
 model_name = "abdulwaheed1/english-to-urdu-translation-mbart"
 
-with gr.Blocks(title="English → Urdu Translator") as app:
-    gr.Markdown(
-        """
-        <div style="text-align:center; padding: 10px;">
-            <h1 style="color:#1e3799;">🕌 English → Urdu Translator</h1>
-            <p style="font-size:18px;">Translate English sentences into beautiful Urdu text using a fine-tuned mBART model.</p>
-        </div>
-        """,
-    )
-
-    with gr.Row():
-        with gr.Column(scale=1):
-            gr.Markdown("⏳ <i>Loading model... please wait 10–20 seconds on first launch.</i>")
-    
-    # Load the model only once (outside function)
-    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 ----
-    input_box = gr.Textbox(
-        label="Enter English Text",
-        placeholder="Type your English sentence here...",
-        lines=2,
-    )
-    output_box = gr.Textbox(
-        label="Urdu Translation",
-        lines=2,
-    )
-
-    example_texts = [
-        ["How are you?"],
-        ["Today is a beautiful day."],
-        ["Where are you going?"],
-        ["I am learning Artificial Intelligence."],
-        ["Thank you very much!"]
-    ]
-
-    gr.Interface(
-        fn=translate_to_urdu,
-        inputs=input_box,
-        outputs=output_box,
-        examples=example_texts,
-        title="🕌 English → Urdu Translator",
-        description="Built by Khurram Basharat — powered by mBART model fine-tuned for English to Urdu translation.",
-        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;
-            }
-        """,
-    ).launch()
+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()