Remove comments and docstrings

app.py

@@ -1,25 +1,16 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the model pipeline
 MODEL_NAME = "nexusbert/tomato-disease-vit"
 classifier = pipeline("image-classification", model=MODEL_NAME)
 
 def classify_tomato(image):
-    """
-    Classify tomato disease from an image.
-    Returns formatted prediction results.
-    """
     if image is None:
         return "Please upload an image"
     
-    # Get predictions
     predictions = classifier(image)
-    
-    # Sort by confidence
     predictions = sorted(predictions, key=lambda x: x['score'], reverse=True)
     
-    # Format output
     result = "## 🍅 Classification Results\n\n"
     result += f"**Top Prediction:** {predictions[0]['label']}\n\n"
     result += f"**Confidence:** {predictions[0]['score']*100:.2f}%\n\n"
@@ -29,7 +20,6 @@ def classify_tomato(image):
     
     return result
 
-# Create Gradio interface using simple Interface API
 demo = gr.Interface(
     fn=classify_tomato,
     inputs=gr.Image(type="pil", label="Upload Tomato Leaf Image"),