Update app.py

app.py

@@ -1,73 +1,48 @@
 import gradio as gr
+import torch
 from transformers import MarianMTModel, MarianTokenizer
 
-# Load pre-trained models
+# Ensure required libraries are installed
+import os
+os.system("pip install sentencepiece")
+
+# Load models and tokenizers
 model_en_to_ur = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-en-ur")
 tokenizer_en_to_ur = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ur")
 
 model_ur_to_en = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-ur-en")
 tokenizer_ur_to_en = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ur-en")
 
+# Function to translate text
 def translate(text, direction):
-    """Translates text based on selected direction."""
-    if direction == "English → Urdu":
+    if direction == "English to Urdu":
         tokenizer, model = tokenizer_en_to_ur, model_en_to_ur
     else:
         tokenizer, model = tokenizer_ur_to_en, model_ur_to_en
 
+    # Tokenize input text
     inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
-    translated = model.generate(**inputs)
-    return tokenizer.batch_decode(translated, skip_special_tokens=True)[0]
-
-# Custom CSS for Better UI
-custom_css = """
-h1 {
-    text-align: center;
-    font-size: 2em;
-    color: #007BFF;
-}
-
-.gradio-container {
-    font-family: 'Arial', sans-serif;
-    background-color: #f9f9f9;
-    padding: 20px;
-    border-radius: 10px;
-}
-
-.input-container textarea {
-    font-size: 16px !important;
-    border-radius: 12px !important;
-    border: 2px solid #007BFF !important;
-}
-
-.button {
-    background-color: #007BFF !important;
-    color: white !important;
-    font-size: 16px;
-    border-radius: 10px !important;
-    padding: 10px 20px !important;
-}
-
-.output-container {
-    background-color: white;
-    padding: 15px;
-    border-radius: 12px;
-    border: 1px solid #ddd;
-}
-"""
-
-# Gradio UI
-with gr.Blocks(css=custom_css) as app:
-    gr.Markdown("# 🌍 **English ↔ Urdu Translator**")
-    gr.Markdown("Translate text between English and Urdu effortlessly!")
-
-    with gr.Row():
-        text_input = gr.Textbox(placeholder="Type text here...", label="Enter Text", lines=3)
-        direction = gr.Radio(["English → Urdu", "Urdu → English"], label="Translation Direction", value="English → Urdu")
-
-    translate_button = gr.Button("🔄 Translate")
-    output_text = gr.Textbox(label="Translated Text", interactive=False)
-
-    translate_button.click(translate, inputs=[text_input, direction], outputs=output_text)
 
-app.launch()
+    # Generate translation
+    with torch.no_grad():
+        translated = model.generate(**inputs)
+
+    # Decode output text
+    output = tokenizer.decode(translated[0], skip_special_tokens=True)
+    return output
+
+# Gradio interface
+interface = gr.Interface(
+    fn=translate,
+    inputs=[
+        gr.Textbox(label="Enter Text"),
+        gr.Radio(["English to Urdu", "Urdu to English"], label="Translation Direction", value="English to Urdu"),
+    ],
+    outputs=gr.Textbox(label="Translated Text"),
+    title="English ↔ Urdu Translator",
+    description="Translate text between English and Urdu using a neural machine translation model.",
+)
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    interface.launch()