Update app.py

app.py

@@ -7,7 +7,7 @@ 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, "", "", "", "", "", "", "", ""
+    return "", 0, "", [], "", "", "", "", 0, "", "", "", "", "", ""
 
 custom_css = """
 /* General Styling */
@@ -184,11 +184,9 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
                 paraphrased_toxicity_output = gr.Textbox(label="Paraphrased Toxicity Score", placeholder="Toxicity score will appear here...")
                 paraphrased_bias_output = gr.Textbox(label="Paraphrased Bias Score", placeholder="Bias score will appear here...")
                 semantic_similarity_output = gr.Textbox(label="Semantic Similarity", placeholder="Semantic similarity score will appear here...")
-                emotion_shift_output = gr.Textbox(label="Emotion Shift", placeholder="Emotion shift will appear here...")
                 empathy_score_output = gr.Textbox(label="Empathy Score", placeholder="Empathy score will appear here...")
                 bleu_score_output = gr.Textbox(label="BLEU Score", placeholder="BLEU score will appear here...")
                 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...")
 
     with gr.Row():
         with gr.Column(scale=1):
@@ -212,8 +210,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             prediction, confidence, color, toxicity_score, bias_score,
             paraphrased_comment, paraphrased_prediction, paraphrased_confidence,
             paraphrased_color, paraphrased_toxicity_score, paraphrased_bias_score,
-            semantic_similarity, emotion_shift, empathy_score,
-            bleu_score, rouge_scores, entailment_score
+            semantic_similarity, empathy_score, bleu_score, rouge_scores
         ) = classify_toxic_comment(comment)
         
         history.append({
@@ -228,11 +225,9 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             "paraphrased_toxicity_score": paraphrased_toxicity_score,
             "paraphrased_bias_score": paraphrased_bias_score,
             "semantic_similarity": semantic_similarity,
-            "emotion_shift": emotion_shift,
             "empathy_score": empathy_score,
             "bleu_score": bleu_score,
-            "rouge_scores": rouge_scores,
-            "entailment_score": entailment_score
+            "rouge_scores": rouge_scores
         })
         
         threshold_message = "High Confidence" if confidence >= 0.7 else "Low Confidence"
@@ -251,14 +246,12 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             if paraphrased_prediction else ""
         )
         semantic_similarity_display = f"{semantic_similarity} (Scale: 0 to 1, higher is better)" if semantic_similarity is not None else "N/A"
-        emotion_shift_display = emotion_shift if emotion_shift else "N/A"
         empathy_score_display = f"{empathy_score} (Scale: 0 to 1, higher indicates more empathy)" if empathy_score is not None else "N/A"
         bleu_score_display = f"{bleu_score} (Scale: 0 to 1, higher is better)" if bleu_score is not None else "N/A"
         rouge_scores_display = (
             f"ROUGE-1: {rouge_scores['rouge1']}, ROUGE-2: {rouge_scores['rouge2']}, ROUGE-L: {rouge_scores['rougeL']}"
             if rouge_scores else "N/A"
         )
-        entailment_score_display = f"{entailment_score} (Scale: 0 to 1, higher indicates better consistency)" if entailment_score is not None else "N/A"
 
         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>"
@@ -268,8 +261,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             toxicity_display, bias_display,
             paraphrased_comment_display, paraphrased_prediction_display, paraphrased_confidence_display,
             paraphrased_toxicity_display, paraphrased_bias_display, paraphrased_label_html,
-            semantic_similarity_display, emotion_shift_display, empathy_score_display,
-            bleu_score_display, rouge_scores_display, entailment_score_display
+            semantic_similarity_display, empathy_score_display, bleu_score_display, rouge_scores_display
         )
 
     def handle_feedback(feedback, comment):
@@ -282,7 +274,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             "Paraphrasing... <span class='loading'>⏳</span>", "Calculating... <span class='loading'>⏳</span>", 0, 
             "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>", 
             "Calculating... <span class='loading'>⏳</span>", "Calculating... <span class='loading'>⏳</span>"
         ),
         inputs=[],
@@ -291,8 +282,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             toxicity_output, bias_output,
             paraphrased_comment_output, paraphrased_prediction_output, paraphrased_confidence_output,
             paraphrased_toxicity_output, paraphrased_bias_output, paraphrased_label_display,
-            semantic_similarity_output, emotion_shift_output, empathy_score_output,
-            bleu_score_output, rouge_scores_output, entailment_score_output
+            semantic_similarity_output, empathy_score_output, bleu_score_output, rouge_scores_output
         ]
     ).then(
         fn=handle_classification,
@@ -302,8 +292,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             toxicity_output, bias_output,
             paraphrased_comment_output, paraphrased_prediction_output, paraphrased_confidence_output,
             paraphrased_toxicity_output, paraphrased_bias_output, paraphrased_label_display,
-            semantic_similarity_output, emotion_shift_output, empathy_score_output,
-            bleu_score_output, rouge_scores_output, entailment_score_output
+            semantic_similarity_output, empathy_score_output, bleu_score_output, rouge_scores_output
         ]
     ).then(
         fn=lambda prediction, confidence, html: html,
@@ -328,8 +317,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
             comment_input, confidence_output, label_display, history_output, toxicity_output, bias_output,
             paraphrased_comment_output, paraphrased_prediction_output, paraphrased_confidence_output,
             paraphrased_toxicity_output, paraphrased_bias_output, paraphrased_label_display,
-            semantic_similarity_output, emotion_shift_output, empathy_score_output,
-            bleu_score_output, rouge_scores_output, entailment_score_output
+            semantic_similarity_output, empathy_score_output, bleu_score_output, rouge_scores_output
         ]
     )