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| import gradio as gr | |
| import logging | |
| from config import config | |
| from app import SentimentApp | |
| # Optimized Gradio Interface | |
| def create_interface(): | |
| """Create comprehensive Gradio interface with optimizations""" | |
| app = SentimentApp() | |
| with gr.Blocks(theme=gr.themes.Soft(), title="Multilingual Sentiment Analyzer") as demo: | |
| gr.Markdown("# 🌍 Multilingual Sentiment Analyzer") | |
| gr.Markdown("AI-powered sentiment analysis with SHAP & LIME explainable AI features") | |
| with gr.Tab("Single Analysis"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| text_input = gr.Textbox( | |
| label="Enter Text for Analysis", | |
| placeholder="Enter your text in any supported language...", | |
| lines=5 | |
| ) | |
| with gr.Row(): | |
| language_selector = gr.Dropdown( | |
| choices=list(config.SUPPORTED_LANGUAGES.values()), | |
| value="Auto Detect", | |
| label="Language" | |
| ) | |
| theme_selector = gr.Dropdown( | |
| choices=list(config.THEMES.keys()), | |
| value="default", | |
| label="Theme" | |
| ) | |
| with gr.Row(): | |
| clean_text_cb = gr.Checkbox(label="Clean Text", value=False) | |
| remove_punct_cb = gr.Checkbox(label="Remove Punctuation", value=False) | |
| remove_nums_cb = gr.Checkbox(label="Remove Numbers", value=False) | |
| analyze_btn = gr.Button("Analyze", variant="primary", size="lg") | |
| gr.Examples( | |
| examples=app.examples, | |
| inputs=text_input, | |
| cache_examples=False | |
| ) | |
| with gr.Column(): | |
| result_output = gr.Textbox(label="Analysis Results", lines=8) | |
| with gr.Row(): | |
| gauge_plot = gr.Plot(label="Sentiment Gauge") | |
| probability_plot = gr.Plot(label="Probability Distribution") | |
| # FIXED Advanced Analysis Tab | |
| with gr.Tab("Advanced Analysis"): | |
| gr.Markdown("## Explainable AI Analysis") | |
| gr.Markdown("**SHAP and LIME analysis with FIXED implementation** - now handles text input correctly!") | |
| with gr.Row(): | |
| with gr.Column(): | |
| advanced_text_input = gr.Textbox( | |
| label="Enter Text for Advanced Analysis", | |
| placeholder="Enter text to analyze with SHAP and LIME...", | |
| lines=6, | |
| value="This movie is absolutely fantastic and amazing!" | |
| ) | |
| with gr.Row(): | |
| advanced_language = gr.Dropdown( | |
| choices=list(config.SUPPORTED_LANGUAGES.values()), | |
| value="Auto Detect", | |
| label="Language" | |
| ) | |
| num_samples_slider = gr.Slider( | |
| minimum=50, | |
| maximum=300, | |
| value=100, | |
| step=25, | |
| label="Number of Samples", | |
| info="Lower = Faster, Higher = More Accurate" | |
| ) | |
| with gr.Row(): | |
| shap_btn = gr.Button("SHAP Analysis", variant="primary") | |
| lime_btn = gr.Button("LIME Analysis", variant="secondary") | |
| gr.Markdown(""" | |
| **📊 Analysis Methods:** | |
| - **SHAP**: Token-level importance scores using Text masker | |
| - **LIME**: Feature importance through text perturbation | |
| **⚡ Expected Performance:** | |
| - 50 samples: ~10-20s | 100 samples: ~20-40s | 200+ samples: ~40-80s | |
| """) | |
| with gr.Column(): | |
| advanced_results = gr.Textbox(label="Analysis Summary", lines=12) | |
| with gr.Row(): | |
| advanced_plot = gr.Plot(label="Feature Importance Visualization") | |
| with gr.Tab("Batch Analysis"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| file_upload = gr.File( | |
| label="Upload File (CSV/TXT)", | |
| file_types=[".csv", ".txt"] | |
| ) | |
| batch_input = gr.Textbox( | |
| label="Batch Input (one text per line)", | |
| placeholder="Enter multiple texts, one per line...", | |
| lines=10 | |
| ) | |
| with gr.Row(): | |
| batch_language = gr.Dropdown( | |
| choices=list(config.SUPPORTED_LANGUAGES.values()), | |
| value="Auto Detect", | |
| label="Language" | |
| ) | |
| batch_theme = gr.Dropdown( | |
| choices=list(config.THEMES.keys()), | |
| value="default", | |
| label="Theme" | |
| ) | |
| with gr.Row(): | |
| batch_clean_cb = gr.Checkbox(label="Clean Text", value=False) | |
| batch_punct_cb = gr.Checkbox(label="Remove Punctuation", value=False) | |
| batch_nums_cb = gr.Checkbox(label="Remove Numbers", value=False) | |
| with gr.Row(): | |
| load_file_btn = gr.Button("Load File") | |
| analyze_batch_btn = gr.Button("Analyze Batch", variant="primary") | |
| with gr.Column(): | |
| batch_summary = gr.Textbox(label="Batch Summary", lines=8) | |
| batch_results_df = gr.Dataframe( | |
| label="Detailed Results", | |
| headers=["Index", "Text", "Sentiment", "Confidence", "Language", "Word_Count"], | |
| datatype=["number", "str", "str", "str", "str", "number"] | |
| ) | |
| with gr.Row(): | |
| batch_plot = gr.Plot(label="Batch Analysis Summary") | |
| confidence_dist_plot = gr.Plot(label="Confidence Distribution") | |
| with gr.Tab("History & Analytics"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Row(): | |
| refresh_history_btn = gr.Button("Refresh History") | |
| clear_history_btn = gr.Button("Clear History", variant="stop") | |
| status_btn = gr.Button("Get Status") | |
| history_theme = gr.Dropdown( | |
| choices=list(config.THEMES.keys()), | |
| value="default", | |
| label="Dashboard Theme" | |
| ) | |
| with gr.Row(): | |
| export_csv_btn = gr.Button("Export CSV") | |
| export_json_btn = gr.Button("Export JSON") | |
| with gr.Column(): | |
| history_status = gr.Textbox(label="History Status", lines=8) | |
| history_dashboard = gr.Plot(label="History Analytics Dashboard") | |
| with gr.Row(): | |
| csv_download = gr.File(label="CSV Download", visible=True) | |
| json_download = gr.File(label="JSON Download", visible=True) | |
| # Event Handlers | |
| # Single Analysis | |
| analyze_btn.click( | |
| app.analyze_single, | |
| inputs=[text_input, language_selector, theme_selector, | |
| clean_text_cb, remove_punct_cb, remove_nums_cb], | |
| outputs=[result_output, gauge_plot, probability_plot] | |
| ) | |
| # FIXED Advanced Analysis with sample size control | |
| shap_btn.click( | |
| app.analyze_with_shap, | |
| inputs=[advanced_text_input, advanced_language, num_samples_slider], | |
| outputs=[advanced_results, advanced_plot] | |
| ) | |
| lime_btn.click( | |
| app.analyze_with_lime, | |
| inputs=[advanced_text_input, advanced_language, num_samples_slider], | |
| outputs=[advanced_results, advanced_plot] | |
| ) | |
| # Batch Analysis | |
| load_file_btn.click( | |
| app.data_handler.process_file, | |
| inputs=file_upload, | |
| outputs=batch_input | |
| ) | |
| analyze_batch_btn.click( | |
| app.analyze_batch, | |
| inputs=[batch_input, batch_language, batch_theme, | |
| batch_clean_cb, batch_punct_cb, batch_nums_cb], | |
| outputs=[batch_summary, batch_results_df, batch_plot, confidence_dist_plot] | |
| ) | |
| # History & Analytics | |
| refresh_history_btn.click( | |
| app.plot_history, | |
| inputs=history_theme, | |
| outputs=[history_dashboard, history_status] | |
| ) | |
| clear_history_btn.click( | |
| lambda: f"Cleared {app.history.clear()} entries", | |
| outputs=history_status | |
| ) | |
| status_btn.click( | |
| app.get_history_status, | |
| outputs=history_status | |
| ) | |
| export_csv_btn.click( | |
| lambda: app.data_handler.export_data(app.history.get_all(), 'csv'), | |
| outputs=[csv_download, history_status] | |
| ) | |
| export_json_btn.click( | |
| lambda: app.data_handler.export_data(app.history.get_all(), 'json'), | |
| outputs=[json_download, history_status] | |
| ) | |
| return demo | |
| # Application Entry Point | |
| if __name__ == "__main__": | |
| logging.basicConfig( | |
| level=logging.INFO, | |
| format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' | |
| ) | |
| try: | |
| demo = create_interface() | |
| demo.launch( | |
| share=True, | |
| server_name="0.0.0.0", | |
| server_port=7860, | |
| show_error=True | |
| ) | |
| except Exception as e: | |
| logging.error(f"Failed to launch application: {e}") | |
| raise |