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| """Start the ReviewGuard web app. | |
| Run it locally with `python app.py`. | |
| Add `--share` for a temporary public link to this computer. | |
| The same file starts the app on Hugging Face Spaces. | |
| """ | |
| import argparse | |
| import gradio as gr | |
| from reviewguard import config | |
| from reviewguard.analyzer import ReviewAnalyzer | |
| from reviewguard.ui import about_tab, batch_tab, lab_tab, performance_tab, triage_tab | |
| HEADER = """ | |
| # 🛡️ ReviewGuard | |
| **AI triage for retail reviews.** Reads what the customer wrote, what they rated and what their | |
| photo shows, then flags the orders that need action and routes them to the right team. | |
| """ | |
| def build_app() -> gr.Blocks: | |
| """Load the models and assemble every tab of the app. | |
| Stops with a clear message if the models have not been trained yet. | |
| """ | |
| if not config.SENTIMENT_MODEL_DIR.exists(): | |
| raise SystemExit( | |
| "Trained models not found in artifacts/models. " | |
| "Run `python pipeline.py fetch-models` to download them, " | |
| "or retrain with the README steps." | |
| ) | |
| analyzer = ReviewAnalyzer() | |
| with gr.Blocks(title="ReviewGuard") as app: | |
| gr.Markdown(HEADER) | |
| with gr.Tab("Review triage"): | |
| triage_tab.build(analyzer) | |
| with gr.Tab("Batch triage"): | |
| batch_tab.build(analyzer) | |
| with gr.Tab("Model lab"): | |
| lab_tab.build(analyzer) | |
| with gr.Tab("Model performance"): | |
| performance_tab.build() | |
| with gr.Tab("How it works"): | |
| about_tab.build() | |
| return app | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser(description="Start the ReviewGuard web app.") | |
| parser.add_argument("--share", action="store_true", help="create a temporary public link") | |
| args = parser.parse_args() | |
| # The artifacts folder holds the example files and report figures the app displays. | |
| build_app().launch( | |
| theme=gr.themes.Soft(), share=args.share, allowed_paths=[str(config.ARTIFACTS_DIR)] | |
| ) | |