docs-anonymizer 0.2.7

Offline document anonymizer for legal teams

anonymizer

Offline document anonymizer for legal teams. Replaces personally identifiable information (PII) in documents with structured tokens before sending them to external AI services.

Status: MVP-0 release candidate.

What it does

Drag a file (docx / pdf with text layer / xlsx) into the local web UI and get an anonymized document where:

• Names, companies, financial details, addresses, emails, phones are replaced with structured tokens like [Person_1], [Company_1], [ADDRESS_1], ...
• Document metadata is cleared
• No network calls during processing — runs entirely on your machine

Then send the result to your AI tool of choice.

MVP-0 scope

• Formats: docx, pdf with text layer, xlsx
• Languages: Russian, English (NER); language-agnostic detectors for emails, phones, IBAN, cards, IP/MAC/URL, dates, geocoordinates
• Platforms: Windows + macOS
• UI: local web app at 127.0.0.1 in your browser
• Install: single curl one-liner → uv tool install docs-anonymizer

OCR for scanned PDFs, password-protected files, additional languages — planned for later iterations (MVP-1+).

Installation

# macOS / Linux
curl -fsSL https://anonymizer.site/install.sh | sh

# Windows (PowerShell)
iwr -useb https://anonymizer.site/install.ps1 | iex

Then run anonymize — your browser will open at http://127.0.0.1:<port>.

Stack

Python 3.11+, FastAPI + htmx, spaCy + Natasha, PyMuPDF, python-docx, openpyxl, lxml. Full details in the technical spec.

Architecture

Three-layer design — core (headless Python library), cli, webapp (FastAPI on loopback) — plus testkit for synthetic test corpus generation and feedback loop tooling. Detectors are pluggable; language packs are drop-in. Manual masking + audit logging without PII leakage.

Licenses

The project is released under AGPL-3.0 because it depends on PyMuPDF (AGPL). All other dependencies are permissive open-source (MIT / Apache 2.0 / BSD / MPL). The source distribution published with each release contains the project source needed to satisfy AGPL source-availability obligations.

A page in the application UI will list all bundled libraries and models with their individual licenses.