Update app.py

app.py

@@ -2,11 +2,13 @@
 import gradio as gr
 from classifier import classify_toxic_comment
 
-# Clear function for resetting the UI
 def clear_inputs():
+    """
+    Reset all UI input and output fields to their default values.
+    Returns a tuple of empty or default values for all UI components.
+    """
     return "", 0, "", [], "", "", "", "", 0, "", "", "", "", "", "", "", ""
 
-# Custom CSS for styling
 custom_css = """
 /* General Styling */
 body {
@@ -121,9 +123,7 @@ h3 {
 }
 """
 
-# Main UI function
 with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
-    # Header Section
     gr.Markdown(
         """
         # Toxic Comment Classifier
@@ -131,7 +131,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
         """
     )
 
-    # Input Section
     with gr.Row():
         with gr.Column(scale=4, min_width=600):
             comment_input = gr.Textbox(
@@ -154,9 +153,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
         label="Try these examples:"
     )
 
-    # Output Section
     with gr.Row():
-        # Left Column: Original Comment Metrics
         with gr.Column(scale=1, min_width=400):
             gr.Markdown("### Original Comment Analysis")
             prediction_output = gr.Textbox(label="Prediction", placeholder="Prediction will appear here...")
@@ -172,7 +169,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             bias_output = gr.Textbox(label="Bias Score", placeholder="Bias score will appear here...")
             threshold_display = gr.HTML()
 
-        # Right Column: Paraphrased Output (if Toxic)
         with gr.Column(scale=1, min_width=400):
             with gr.Accordion("Paraphrased Output (if Toxic)", open=False):
                 paraphrased_comment_output = gr.Textbox(label="Paraphrased Comment", placeholder="Paraphrased comment will appear here if the input is toxic...")
@@ -194,7 +190,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
                 rouge_scores_output = gr.Textbox(label="ROUGE Scores", placeholder="ROUGE scores will appear here...")
                 entailment_score_output = gr.Textbox(label="Entailment Score (Factual Consistency)", placeholder="Entailment score will appear here...")
 
-    # History and Feedback Sections
     with gr.Row():
         with gr.Column(scale=1):
             with gr.Accordion("Prediction History", open=False):
@@ -265,7 +260,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
         )
         entailment_score_display = f"{entailment_score} (Scale: 0 to 1, higher indicates better consistency)" if entailment_score is not None else "N/A"
 
-        # Add visual indicator to the prediction
         prediction_class = "toxic-indicator" if "Toxic" in prediction else "nontoxic-indicator"
         prediction_html = f"<span class='{prediction_class}' style='color: {color}; font-size: 20px; font-weight: bold;'>{prediction}</span>"
 
@@ -290,7 +284,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             "Calculating... <span class='loading'>⏳</span>", "Calculating... <span class='loading'>⏳</span>", 
             "Calculating... <span class='loading'>⏳</span>", "Calculating... <span class='loading'>⏳</span>", 
             "Calculating... <span class='loading'>⏳</span>", "Calculating... <span class='loading'>⏳</span>"
-        ),  # Show loading state with animation
+        ),
         inputs=[],
         outputs=[
             prediction_output, confidence_output, label_display, history_output, threshold_display, threshold_display,