| ---
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| title: GuardPII GLiNER2 Demo
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| emoji: 🔎
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| colorFrom: blue
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| colorTo: green
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| sdk: gradio
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| sdk_version: 4.44.1
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| app_file: app.py
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| pinned: false
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| ---
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| # GuardPII GLiNER2 Demo
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| Gradio demo for PII extraction with GLiNER2 plus the high-precision rulebase used by the project prediction pipeline.
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| ## Inputs
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| - Raw text
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| - `.docx` files via `python-docx`
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| - `.pdf` files via LlamaParse by default, with optional local parsers: `pdfplumber`, `pymupdf`, `pypdf`
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| ## Hugging Face Space Setup
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| Upload the contents of this `DEMO` folder to a Hugging Face Space.
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| Set Space secrets or variables as needed:
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| - `LLAMA_CLOUD_API_KEY`: required when using the default `llamaparse` PDF parser
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| - `HF_TOKEN`: optional, needed only if the selected GLiNER2 model is private
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| - `MODEL_ID`: optional default model ID, defaults to `AITeamUIT/gliner2-multi-v1-3e-20260514`
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| - `PDF_BACKEND`: optional default PDF parser, defaults to `llamaparse`
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| - `THRESHOLD`: optional default confidence threshold, defaults to `0.5`
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| The app caches loaded models, so the first run may be slow while the model downloads and initializes.
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