update

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from ui.dataset_input import create_dataset_input, load_example_dataset
 from ui.analysis_screen import create_analysis_screen
 from visualization.bow_visualizer import process_and_visualize_analysis
+from visualization.bias_visualizer import process_and_visualize_bias_analysis
 import nltk
 import os
 import logging
@@ -502,6 +503,29 @@ def create_app():
                                     for category, diff in differences.items()
                                 ])
                     
+                    # Add visualization handling for Bias Detection
+                    elif selected_analysis == "Bias Detection" and "bias_detection" in analyses:
+                        # Use the bias visualization function to create components
+                        visualization_components = process_and_visualize_bias_analysis(analysis_results)
+                        
+                        # Set up visibility and components for display
+                        return (
+                            analysis_results,  # analysis_results_state
+                            False,  # analysis_output visibility  
+                            True,  # visualization_area_visible
+                            gr.update(visible=True),  # analysis_title
+                            gr.update(visible=True, value=f"## Analysis of Prompt: \"{prompt[:100]}...\""),  # prompt_title
+                            gr.update(visible=True, value=f"### Comparing responses from {models[0]} and {models[1]}"),  # models_compared
+                            gr.update(visible=False),  # model1_title
+                            gr.update(visible=False),  # model1_words
+                            gr.update(visible=False),  # model2_title
+                            gr.update(visible=False),  # model2_words
+                            gr.update(visible=False),  # similarity_metrics_title
+                            gr.update(visible=False),  # similarity_metrics
+                            False,  # status_message_visible
+                            gr.update(visible=False)  # status_message
+                        )                    
+
                     # If we don't have visualization data from any analysis
                     if not visualization_area_visible:
                         return (