How to build scalable web apps with OpenAI's Privacy Filter

OpenAI released Privacy Filter on the Hub this week: an open-source personally-identifiable information (PII) detector that labels text across eight categories in a single forward pass over a 128k context. Model card. We spent a few hours building with it and landed on three apps that each reveals a different slice of what it can do.

Document Privacy Explorer: drop in a PDF or DOCX, read the document back with every PII span highlighted in place.
Image Anonymizer: upload an image, get it back with redacted black bars over names, emails, and account numbers. The image is also editable on a canvas so you can make your own annotations before downloading.
SmartRedact Paste: paste sensitive text, share a public URL that serves the redacted version, keep a private reveal link for yourself.

All three are built on gradio.Server, which lets you pair custom HTML/JS frontends with Gradio's queueing, ZeroGPU allocation, and gradio_client SDK. In all these apps, gradio.Server plays the same backend role, and that consistency is exactly what makes it really powerful.

The model

Privacy Filter is a 1.5B-parameter model with 50M active parameters, permissively licensed under Apache 2.0. PII categories are private_person, private_address, private_email, private_phone, private_url, private_date, account_number, secret. Context is 128,000 tokens. Achieves state-of-the-art performance on the PII-Masking-300k benchmark. Full numbers and methodology are in the official release blog.

1. Document Privacy Explorer

Try it at ysharma/OPF-Document-PII-Explorer.

User problem. You want to read a PII-heavy document (a contract, a resume, an exported chat log) with every detected span highlighted by category, a filter in the sidebar, and a summary dashboard up top. The reading experience should feel like a normal document, not a form.