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| import gradio as gr | |
| import logging | |
| # Set up logging | |
| logger = logging.getLogger('gradio_app.visualization_handler') | |
| def create_visualization_components(): | |
| """ | |
| Creates all the visualization components used in the analysis tab | |
| Returns: | |
| list: A list of all gradio components for visualization | |
| """ | |
| bias_visualizations = gr.Markdown(visible=False) | |
| # Pre-create visualization components (initially hidden) | |
| visualization_area_visible = gr.Checkbox(value=False, visible=False, label="Visualization Visible") | |
| analysis_title = gr.Markdown("## Analysis Results", visible=False) | |
| prompt_title = gr.Markdown(visible=False) | |
| models_compared = gr.Markdown(visible=False) | |
| # Container for model 1 words | |
| model1_title = gr.Markdown(visible=False) | |
| model1_words = gr.Markdown(visible=False) | |
| # Container for model 2 words | |
| model2_title = gr.Markdown(visible=False) | |
| model2_words = gr.Markdown(visible=False) | |
| # Similarity metrics | |
| similarity_metrics_title = gr.Markdown("### Similarity Metrics", visible=False) | |
| similarity_metrics = gr.Markdown(visible=False) | |
| # Status or error message area | |
| status_message_visible = gr.Checkbox(value=False, visible=False, label="Status Message Visible") | |
| status_message = gr.Markdown(visible=False) | |
| # Create bias visualization container (initially hidden) | |
| with gr.Column(visible=False) as bias_visualizations: | |
| gr.Markdown("### Bias Analysis Visualizations") | |
| # This will be populated dynamically | |
| # Return all components as a list | |
| return [ | |
| analysis_results_state := gr.State({}), | |
| analysis_output := gr.JSON(visible=False), | |
| visualization_area_visible, | |
| analysis_title, | |
| prompt_title, | |
| models_compared, | |
| model1_title, | |
| model1_words, | |
| model2_title, | |
| model2_words, | |
| similarity_metrics_title, | |
| similarity_metrics, | |
| status_message_visible, | |
| status_message, | |
| bias_visualizations | |
| ] | |
| def process_and_visualize_bias_analysis(analysis_results): | |
| """ | |
| Wrapper for bias visualization function from visualization.bias_visualizer | |
| Args: | |
| analysis_results (dict): The analysis results | |
| Returns: | |
| list: Components for bias visualization | |
| """ | |
| from visualization.bias_visualizer import process_and_visualize_bias_analysis | |
| return process_and_visualize_bias_analysis(analysis_results) | |
| def process_and_visualize_ngram_analysis(analysis_results): | |
| """ | |
| Wrapper for n-gram visualization function from visualization.ngram_visualizer | |
| Args: | |
| analysis_results (dict): The analysis results | |
| Returns: | |
| list: Components for n-gram visualization | |
| """ | |
| from visualization.ngram_visualizer import process_and_visualize_ngram_analysis | |
| return process_and_visualize_ngram_analysis(analysis_results) | |
| def process_and_visualize_topic_analysis(analysis_results): | |
| """ | |
| Wrapper for topic modeling visualization function from visualization.topic_visualizer | |
| Args: | |
| analysis_results (dict): The analysis results | |
| Returns: | |
| list: Components for topic visualization | |
| """ | |
| from visualization.topic_visualizer import process_and_visualize_topic_analysis | |
| return process_and_visualize_topic_analysis(analysis_results) |