gh0stkey

gh0stkey / opf-privacy-filter

Public

Docker service for OpenAI Privacy Filter (PII redaction API)

12
1
100% credibility
Found Apr 23, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

This repository offers a ready-to-run service that detects and removes personal identifiable information from text inputs.

How It Works

1
🔍 Find the privacy helper

You hear about a simple tool that spots and hides personal details like names or emails in your messages.

2
📥 Get and start it

You download the ready package and launch it on your computer, where it quietly prepares itself.

3
⏳ It wakes up

Give it a minute to get ready, and soon it's listening for your texts on your local machine.

4
🩺 Quick check

You confirm everything is working perfectly with a simple hello message.

5
Clean your texts
📝
One message

Send a single text and get back a safe version with private parts hidden.

📚
Several messages

Upload a list of texts and receive them all cleaned up together.

🛡️ Privacy secured

Your messages are now safe to share, with no personal info accidentally revealed.

Sign up to see the full architecture

4 more

Sign Up Free

Star Growth

See how this repo grew from 12 to 12 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is opf-privacy-filter?

This Python Docker service turns OpenAI's Privacy Filter into a ready-to-run HTTP API for detecting and redacting PII like names, emails, and SSNs from text. Pull the image from the Docker GitHub registry with docker pull ghcr.io/gh0stkey/opf-privacy-filter:latest, then launch via docker run on port 8000 or docker-compose up for persistent restarts. It offers endpoints for health checks, single-text redaction, text-only output, and batch processing, with CPU or GPU acceleration via simple env vars.

Why is it gaining traction?

It skips the hassle of cloning and installing OpenAI's repo by baking the model into a slim Docker image, supporting docker github actions cache and runners for fast CI builds. Developers grab it for one-command deploys that handle docker service create, scale, restart, stop, update, and logs without manual setup. The API's low-latency redaction after a quick initial load beats raw library use in containerized apps.

Who should use this?

Backend teams building APIs that scrub user data before storage or logs, DevOps engineers deploying privacy gates in Docker swarms via docker service starten. Data pipeline owners processing batches of sensitive text in microservices, especially those already using docker github login and registry for images.

Verdict

Grab it for fast PII redaction in Docker workflows—docs cover docker service failed to start troubleshooting and more, making it production-friendly out of the gate. With just 12 stars and 1.0% credibility score, it's immature; prototype first, monitor via docker service logs, but ideal for docker github repo sidecars now.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.