my use case is a bit different though. i started because i wanted to give friends access to specific things in my homelab, but very selectively. like “you can use jellyfin on this one machine, but you can’t ssh, and you can’t even see my other devices”

tailscale is honestly amazing for getting devices connected, i still use it a lot. but once i started trying to do these very specific “this machine can talk to that machine only on this port” kind of setups, it started feeling more complex than it should be, at least for personal use. ACL editor is more confusing when it comes to this. i know we have got option for tags and things, but those are very poorly documented and i haven't found a single tutorial that works nicely.

your userspace approach is really interesting btw, especially the no tun / no root part. makes sense to run it on rigit enterprise environments.

THE PROBLEM: Reading articles from sites like NYT, WSJ, The Atlantic, etc. often hits paywalls. While Archive.ph exists, manually copying URLs and searching is tedious.

THE SOLUTION: ArchiveJump detects when you click article links from 15+ supported news sites and either: - Searches Archive.ph for existing archived versions, OR - Jumps directly to the latest archived version (toggle option)

KEY FEATURES: • Smart detection (only article links, not homepages) • Two modes: search archive.ph OR jump to latest version • Easy toggle controls via popup • Manual "jump" button for any page • Visual feedback (blue/green notifications)

TECHNICAL DETAILS: - Vanilla JavaScript, Manifest V3 - Works on Chrome/Edge - No data collection, settings stored locally - Content script + popup interface

The extension respects sites' content while leveraging publicly available archives. It's particularly useful for research, fact-checking, or when you've hit monthly limits.

GitHub: https://github.com/dhrm1k/ArchiveJump

Install: Load unpacked in Developer Mode (Chrome Web Store submission coming)

Would love feedback on the UX, additional sites to support, or feature suggestions!

Note: This tool uses Archive.ph, which archives publicly available content. Please respect publishers by subscribing if you regularly read their content.

Comments URL: https://news.ycombinator.com/item?id=44405837

Points: 3

# Comments: 0

We built Depict (https://github.com/dhrm1k/depict) - an AI-powered search engine that lets you find Indian museum artworks using natural language descriptions like "painting of fruit" or "blue sculpture."

The project uses OpenAI's CLIP model to understand both text and images, creating embeddings that enable semantic visual search across collections from major Indian museums (National Gallery, National Museum Delhi, Indian Museum Kolkata, etc.).

Key technical details: - Scraped data from Museums of India government portal - Generated CLIP embeddings for artwork images - Built React frontend + Python backend on Modal AI - Similarity search using cosine distance in 512-dimensional space

The live demo currently includes ~2 museums due to compute costs, but the full pipeline is built to handle all 6 major collections. It was inspired by @ekzhang's dispict but focused specifically on making Indian cultural heritage more accessible.

Would love feedback on the search experience and any ideas for improving discoverability of museum collections!

Tech stack: Python, React, CLIP (ViT-B/32), Modal AI, h5py Repo: https://github.com/dhrm1k/depict

Comments URL: https://news.ycombinator.com/item?id=44345420

Points: 1

# Comments: 1