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| import gradio as gr | |
| from pii_transform.api.e2e import PiiTextProcessor | |
| from pii_extract.defs import FMT_CONFIG_PLUGIN | |
| examples = [] | |
| with open("examples.txt", "r") as f: | |
| examples = f.readlines() | |
| examples_truncated = [example[:50] + "..." for example in examples] | |
| language_choices = { | |
| "English": "en", | |
| "Italian": "it", | |
| "Spanish": "es", | |
| "Portugese": "pt", | |
| "Deutsche": "de", | |
| "French": "fr", | |
| } | |
| language_code = "en" | |
| def change_language(language_selection): | |
| global language_code | |
| language_code = language_choices[language_selection] | |
| gr.Info(f"{language_selection} selected") | |
| def process(text, policy): | |
| # Create the object, defining the language to use and the policy | |
| # Further customization is possible by providing a config | |
| if text == "": | |
| print("Empty text field") | |
| gr.Warning("No text present") | |
| return "" | |
| # Custom config to prevent loading of the Presidio plugin | |
| # config = {FMT_CONFIG_PLUGIN: {"piisa-detectors-presidio": {"load": False}}} | |
| proc = PiiTextProcessor( | |
| lang=language_code, default_policy=policy, config="config.json" | |
| ) | |
| # Process a text buffer and get the transformed buffer | |
| outbuf = proc(text) | |
| return outbuf | |
| def get_full_example(idx): | |
| return examples[idx] | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(scale=0, min_width=75): | |
| logo = gr.Image("image.jpeg", show_label=False, show_download_button=False) | |
| with gr.Column(): | |
| pass | |
| with gr.Column(scale=0, min_width=200): | |
| lang_picker = gr.Dropdown( | |
| choices=list(language_choices.keys()), | |
| label="Select Language", | |
| value=list(language_choices.keys())[0], | |
| type="value", | |
| ) | |
| lang_picker.select(change_language, inputs=lang_picker, outputs=None) | |
| with gr.Row(): | |
| with gr.Column(scale=2, min_width=400): | |
| text_original = gr.Textbox( | |
| label="Original Text", | |
| lines=10, | |
| placeholder="Enter the text you would like to analyze, or select from one of the examples below", | |
| ) | |
| with gr.Column(scale=0, min_width=25): | |
| pass | |
| with gr.Column(scale=0, min_width=100): | |
| for i in range(3): | |
| with gr.Row(): | |
| pass | |
| redact_btn = gr.Button(value="Redact", variant="primary", size="sm") | |
| anonymize_btn = gr.Button(value="Anonymize", variant="primary", size="sm") | |
| placeholder_btn = gr.Button( | |
| value="Placeholder", variant="primary", size="sm" | |
| ) | |
| with gr.Column(scale=0, min_width=25): | |
| pass | |
| with gr.Column( | |
| scale=2, | |
| min_width=400, | |
| ): | |
| text_redacted = gr.TextArea( | |
| label="Transformed Text", | |
| lines=10, | |
| show_copy_button=True, | |
| interactive=False, | |
| ) | |
| redact_btn.click( | |
| fn=process, | |
| inputs=[ | |
| text_original, | |
| gr.Text(value="redact", visible=False), | |
| ], | |
| outputs=text_redacted, | |
| ) | |
| anonymize_btn.click( | |
| fn=process, | |
| inputs=[ | |
| text_original, | |
| gr.Text(value="synthetic", visible=False), | |
| ], | |
| outputs=text_redacted, | |
| ) | |
| placeholder_btn.click( | |
| fn=process, | |
| inputs=[ | |
| text_original, | |
| gr.Text(value="label", visible=False), | |
| ], | |
| outputs=text_redacted, | |
| ) | |
| with gr.Row(): | |
| example_selector = gr.Dropdown( | |
| examples_truncated, type="index", label="Examples" | |
| ) | |
| example_selector.select( | |
| get_full_example, inputs=example_selector, outputs=text_original | |
| ) | |
| demo.queue().launch() | |