README.md

metadata

title: Alias
emoji: 🫥
colorFrom: gray
colorTo: blue
sdk: static
app_file: index.html
pinned: false
license: mit
short_description: Mask personal data (FR/EN) in the browser before an LLM
models:
  - Gabrielkph/alias-mmbert-small

Alias, public demo

Paste a French or English text: Alias highlights the personal data it finds (names, addresses, e-mails, phones, IBANs, national IDs, birth dates, file numbers) and gives the text back with stable aliases ([PERSON_1], [IBAN_1]), ready to send to an LLM.

The detector runs in your browser. The page downloads the model once (about 600 MB, kept by the browser for later visits) and the ONNX runtime, then masks the text locally: the text is never sent anywhere, and the page's content security policy allows no host but Hugging Face (model files) and jsDelivr (runtime). Still, use fictitious data: this is a demo.

Detector: checksum and keyword rules plus a fine-tuned mmBERT-small (model), the same as the Python package, ported to JavaScript and checked against it on GitHub Actions. Code, results and limits: github.com/gabrielkpo/alias.

Files

• index.html, app.js, style.css: the page; app.js loads transformers.js 4.3.2.
• alias.js: the detector's logic (rules, token windows, masking), ported from src/alias_pii.
• test/: unit tests (npm test) and the parity check against Python (.github/workflows/demo.yml); not uploaded to the Space.