Update app.py

app.py

@@ -1,11 +1,7 @@
-# STEP 1: Install required libraries
-!pip install transformers sentencepiece gradio -q
-
-# STEP 2: Import libraries
 from transformers import MarianMTModel, MarianTokenizer
 import gradio as gr
 
-# STEP 3: Load models and tokenizers for both directions
+# Load models and tokenizers
 en_to_ur_model_name = "Helsinki-NLP/opus-mt-en-ur"
 ur_to_en_model_name = "Helsinki-NLP/opus-mt-ur-en"
 
@@ -15,24 +11,22 @@ en_to_ur_model = MarianMTModel.from_pretrained(en_to_ur_model_name)
 ur_to_en_tokenizer = MarianTokenizer.from_pretrained(ur_to_en_model_name)
 ur_to_en_model = MarianMTModel.from_pretrained(ur_to_en_model_name)
 
-# STEP 4: Translation functions
+# Translation functions
 def translate_en_to_ur(text):
     if not text.strip():
         return "Please enter some English text."
     inputs = en_to_ur_tokenizer(text, return_tensors="pt", padding=True)
     translated = en_to_ur_model.generate(**inputs)
-    urdu_text = en_to_ur_tokenizer.decode(translated[0], skip_special_tokens=True)
-    return urdu_text
+    return en_to_ur_tokenizer.decode(translated[0], skip_special_tokens=True)
 
 def translate_ur_to_en(text):
     if not text.strip():
         return "براہ کرم کچھ اردو متن درج کریں۔"
     inputs = ur_to_en_tokenizer(text, return_tensors="pt", padding=True)
     translated = ur_to_en_model.generate(**inputs)
-    english_text = ur_to_en_tokenizer.decode(translated[0], skip_special_tokens=True)
-    return english_text
+    return ur_to_en_tokenizer.decode(translated[0], skip_special_tokens=True)
 
-# STEP 5: Gradio UI
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## English ↔ Urdu Translator")
 
@@ -48,5 +42,4 @@ with gr.Blocks() as demo:
         ur_button = gr.Button("Translate")
         ur_button.click(fn=translate_ur_to_en, inputs=ur_input, outputs=ur_output)
 
-# STEP 6: Launch
 demo.launch()