I got a banner warning today linking to this page. It was announced a while back, but I either didn't see it or forgot.

We have made the difficult decision to limit the use of LanguageTool’s browser extension to Premium users only. The rise of generative AI has made it more challenging to sustainably monetize our offering. A majority of users use our products for free, and the relatively small percentage of Premium subscribers is all that is subsidizing our continuously increasing server costs. To improve our Premium experience and to sustain our business model, we’ll be making the LanguageTool browser extension available exclusively for paying customers.

The key bit for people who can selfhost:

Yes. If you are a developer, you can still host and run your own instance of LanguageTool’s server. The browser extension will continue to work as it currently does for users who use it with their own server.

I want to host some LLM's locally and use more advanced models. Since new hardware is out of the question, I think I should be able to pull something off buying some yesteryear equipment on ebay etc. Did anybody attempt such a project? Does it scale horizontally? (I.e. can I connext two boxes to overcome single box slowness?)

hey everyone, I wanted to share a project l've been developing for the past two weeks. I had tried to find a minimalist open-source bad-habit tracker, but I didn't like the ones I found or ran into some issues. So I decided to build one using the stack I know best. I added some features like setting a target number of days with a progress bar toward that target, notes and a feed to save articles, news, or video links that help you stay focused on your goal. there's also an option to set a password to access the site, and both light and dark themes.

Gah! This bit me today.

I'm experimenting with switching from Tailscale to Netbird. I was streaming Jellyfin to my TV via netbird and was surprised when it started buffering. Turning down the video quality helped keep the stream going.

Yeah, no wonder. Turns out my video was being streamed via relay because all of the Android apps default to force relayed connections.

I guess they're working out some kinks still... anyway, turning that setting off fixed my streaming latency!

Recent post re: AI as utility

https://www.tomsguide.com/ai/people-will-buy-intelligence-from-us-on-a-meter-chatgpts-ceo-sam-altman-has-critics-worried-with-his-ai-vision

Myself, I'm a fan of local LLM / self hosted ML.... but if you ever needed a clarion call that a hard pivot is coming (soon) for online/ cloud based AI...Altman et al are making some concerning mouth noises (to say nothing of broader concerns with OAI, Anthropic etc).

Right now, I'm sketching out a plan where my Raspberry Pi (always on, 2-3w) uses a magic packet to wake up my modest AI server (Lenovo P330 with Tesla P4) if/when needed (Qwen 3.6-35B-A3B); no point in chugging down 80-100w, 24/7 for no good reason.

If the trend continues the direction it appears to be (increasing costs, environmental impacts etc) then I'd feel a lot better hosting my own as port of first call and replacing simpler tasks with more traditional programs. YMMV.

The default API tooling that comes to your mind is Postman.

Postman is cloud based - the other offline alternatives are on their way to enshittification.

Is there any solution to the problem or we should all default to curl.

Hi folks, my NAS is running on this motherboard: https://rog.asus.com/motherboards/rog-crosshair/rog-crosshair-vi-extreme-model/spec/

I currently have the following:

• M.2 NVME Boot Drive 1TB SSD
• M.2 NVME App Drive SSD
• SATA HDD Pools
• SATA SSD Pools
• 2x GTX 1080s SLI
• 1 USB 3.1 PCIe card
• 32 GB DDR4 (wish I had bought 64Gb before prices went crazy, but it's perfectly manageable)

As you can probably tell, this was a gaming PC at one point, but now I have it in a massive case, so it's really easy to get in there and mess with stuff on my home rig.

Here's my quandry: I currently have a 1TB M.2 drive as my boot drive of which ~16Gb is used. SSDs are obscenely expensive right now and I'm out of room for games. I've read online that you can use Intel Optane memory as a boot drive.

This unit in particularly was recommended: https://www.amazon.com/Intel-Optane-Memory-Xpoint-Retail/dp/B078ZCZ5H9

My question is this, and it sounds a bit silly for someone who can self host to not know this, but how do I insert the optane memory and is it compatible with my mobo? I see it has a PCI 3.0 connection type but it has a little half-moon screw divot on the end like an M.2 drive. Do I just push a drive like this upright into one of the PCIe slots or does it have to go into that second m.2 slot the motherboard specs show supports PCI 3.0. I'm trying to avoid using the second M.2 slot since I might want to add a second SSD for apps later on as I already get an earful whenever the Jellyfin goes down. :D Alternatively, I'm considering using the SATA SSD as a boot drive. I've read that once everything is up, it's all loaded into RAM anyway and the boot drive speed is not really important anymore. I can tolerate an extra 15 seconds on startup more a machine that might get rebooted once or twice a week when things are running smoothly. I could give up the USB 3.1 PCIe card as I think there are some headers hooked up to the case ports.

What would you do in my situation?

I am trying to capture costs for starting into homelab/selfhosting.

VPNs, search engines, absolutely everything and anything.

MakeMKV gives you a pile of VOB files. Sonarr wants a clean named MKV in the right folder. The gap between those two is always a manual dance. Figure out which season it is, rename it, drop it in the right place, trigger a rescan.

Discarr fills that gap: it's a small Node.js web UI (no npm packages, pure built-ins) that handles the VIDEO_TS / BDMV / ISO → arr import chain.

What it does:

• Scans disc structure automatically (VIDEO_TS, BDMV, multi-disc, ISO)
• Reads IFO chapter data to split multi-episode DVD discs correctly
• Browser UI to map disc titles to the right Sonarr episodes or Radarr movies
• Queues HEVC encodes via ffmpeg or HandBrake (locally or over SSH to a remote box)
• Notifies Sonarr/Radarr via custom script hooks on import/delete/completion
• Optional: qBittorrent hook triggers a scan on torrent completion; Tdarr ping after encode
• Persistent job queue. restarts resume automatically

Requirements: Node.js 18+, ffmpeg + ffprobe. HandBrake optional. Docker image bundles both plus openssh-client.

Still early, issues and PRs welcome.

Forgejo (primary): https://git.opensourcesolarpunk.com/Circuit-Forge/discarr GitHub (mirror): https://github.com/pyr0ball/discarr

For the longest time, I've been trying to figure out a way to "survive" in this new AI age without having to fork over a ton of money just to keep up. I've tried using local models via Ollama, and while they definitely work to a degree, they're (unsurprisingly) not as good as the big model providers.

The local models tend to

• Forget what they're doing
• Struggle to break larger tasks into smaller ones
• Lose focus easily
• Have weaker coding performance
• Drift over longer sessions

So to improve the reliability of fully local, smaller models (and to keep all my data local and in my own network), I created Coyote.

It's a local-first, batteries-included command line tool and runtime for building and running LLM workflows locally. It's model agnostic and supports things like

• Agents and agent delegation
• Roles/personas
• MCP Servers
• RAG
• Custom tools
• Macros
• Workflow Scripting

A lot of the features it supports are specifically designed to compensate for weaknesses in smaller local models. For example:

• Auto continuation to keep pushing models to completion instead of stopping halfway through problems
• Parallel agent delegation so tasks can be split into smaller, focused scopes
• Workflow-based execution ("If this, do that") for building more reliable and repeatable automations

It also supports the major cloud providers if you want them (which definitely helped while testing 😄), but my long-term goal is simple:

Get as close as possible to Claude Code-style reliability using fully local models.

I'm always open to feedback, questions, or ideas.

Repo: https://github.com/Dark-Alex-17/coyote

cross-posted from: https://discuss.online/post/40322414

Still in progress. Open to suggestions! Current idea is to offer a dark and light mode switch, plus get some fun icons. Want to introduce variations with visual glitches and such, for more of a cyberpunk aesthetic, that can be generated through a pipeline. This is an excuse to learn a lot of little, technical things.

Hi all !
I want to use xcp-ng for my homelab because why not, terraform and I like to use more uncommon tools (it often bites me afterward but it's funnier this way). Right now, I am on a road block because I can't set a management interface, and I can't do it because using DHCP times out and I can't set static IP on my ISP's router. Anyone with an idea ?

Edit : an emergency network reset solved the issue. I think I plugged and unplugged multiple time during the uptime, maybe it caused the issue

I just recently stumbled on this and I've never heard anyone here that uses it. It looks quite interesting. A dash for your Proxmox server.

The live demo looks jammy: https://demo.proxcenter.io/

The docs look quite comprehensive: https://docs.proxcenter.io/

Github: https://github.com/adminsyspro/proxcenter-ui

Runs in a Docker container. There is an community version and an enterprise version. I think I'm going to bump this up the Projects list to the top.

I've been thinking about this more and more. According to the sidebar, this community is "A place to share alternatives to popular online services that can be self-hosted without giving up privacy or locking you into a service you don’t control." Based on that I don't think Plex qualifies.

Privacy: Plex clearly records the metadata of what you watch. When I used it, it would send me a report by email of what my "friends" were watching. Even with that turned off, their services still track telemetry.

Control: Plex has all of it. They can (and do) make unilateral changes to the service, how authentication works, where you can run it, etc.

So I ask, when you are hosting something that is entirely dependent on a commercial entity to function, is Plex really selfhosting in the spirit of this community?

Hello self-hosters,

I have been building Journiv, a self-hosted, privacy-first journaling app for people who want to own their personal memories, journals, mood/activity tracking, photos, and related life data.

A few months ago I added Immich integration, which allows you to browse your Immich library from Journiv and attach photos/videos directly to journal entries. That integration was focused on connecting self-hosted photos and videos to the written story behind them.

I just added the next piece: People Tracking with optional Immich face sync.

The idea is simple:

Immich is great at preserving the photo/video itself. Journiv is meant to preserve the story around it. Now Journiv can also help track who was part of that memory.

With the new People feature, you can create and manage important people in your life family, friends, kids, parents, coworkers, etc. Attach them to journal entries. Later, you can filter your timeline by a person and see the memories you’ve captured with them over time.

If you also use Immich, Journiv can use Immich’s people/face data to make this easier.

When you attach an Immich photo to a Journiv entry, Journiv can check the Immich people/faces associated with that asset. If those Immich people are linked to people you track in Journiv, Journiv can automatically suggest or add them to the journal entry.

The goal is not just to store photos or journal text separately, but to connect them together into a more meaningful personal archive: what happened, when it happened, where it happened, and who was part of it.

Would love feedback from the self-hosted community on this feature.

• Watch the demo video
• Blog post with more context
• Get started: Install Journiv
• Immich integration docs
• Release notes
• Demo images from Pexels

Hey lemmy, I got the app I built for my Frigate instance to a place where I think it's good enough to share. It's currently in testing on the play store. It's a fully native android app built in flutter. DM me your email if you'd like to be added as a tester.

• Live viewing
• Live camera grid
• Sub-stream switching
• Pinch-zoom and pan (with double tap to fullscreen) on all videos (recorded or live)
• Detections and reviews
• Recent detections
• Events feed
• Reviews feed with grouped detection clips
• Recordings
• Timeline scrubbing w/ previews
• Tuned for mobile networks
• Export and download clips directly to your device or share sheet
• Push notifications via UnifiedPush (ntfy and other distributors)
• PTZ controls for supported cameras
• Birdseye view when enabled on the server
• System stats
• Live logs viewer
• Works with HTTP, HTTPS, or HTTPS with self-signed certificates
• Widgets for home screen

link for mobile: https://play.google.com/store/apps/details?id=me.tinius.albatross

link for desktop: https://play.google.com/apps/testing/me.tinius.albatross

Hey everyone,

We've built an open-source, privacy-preserving alternative to Ring cameras using a Raspberry Pi Zero 2W (called Secluso). It uses end-to-end encryption to send videos from the camera to a mobile app, which is available both in Google Play Store and Apple App Store. We also support Obtainium for people that do not wish to use Google Play.

We've put in a lot of effort to make it easy to set up! You can set up our camera on your own Pi in less than 5 minutes with minimal technical expertise using our easy-to-use GUI deploy tool. Here are our setup guide and open source release.

The image shows a Pi in an official Raspberry Pi enclosure that you can use for your camera. We've also been working on a HAT for the Pi to add night vision, audio, temperature monitoring for safety, all in a compact form factor. You can see the HAT and an enclosure for the whole camera in the photo.

We've been working on this for almost 2 years now, and we look forward to we look forward to seeing what you all think! If you're interested in our efforts in general outside of DIY, our main website with our pre-built offering is here: click to see our website

I currently run all my self-hosted apps either on Podman in a VM or in LXCs on Proxmox. For hardware, I'm using a Chinese-made mini computer with an Intel N150 and 16GB of DDR5 RAM that I bought before the whole AI hype started. I also have a Synology NAS that I use mainly for media and photo storage.

I've been thinking about tinkering with Kubernetes in my homelab for a while now (I already use it extensively at work, so I'm quite familiar with it), and I started looking around for used hardware to use as bare metal nodes. Nothing fancy—I'm looking for 1 or 2 mini servers or SFF with at least 16GB of memory and a decent CPU (4–6 cores). But with current prices, even decently priced used hardware (~200–250€) is quite difficult to find in Europe, and most of it is HP stuff with Lenovo being a rare breed around here. I won't even get started on newly bought hardware...

If you've bought hardware in this market recently, how did it go for you? Or are most of you holding out for now, waiting for better times?

GitHub: https://github.com/TechSquidTV/Cliparr

Major Updates:

• HLS Streaming (Now uses the media server's transcoded stream as the default source, which better matches expected behavior)
• Subtitle Burn-in. Use any font on your system to overlay subtitles on the output. Subtitles come from your media server; ensure to download or select them.

I currently have a secondary pool (with raidz2) that I was originally going to use for my important documents, such as storage for Paperless-ngx, as raidz offers corruption detection and repair. The pool is encrypted.

However, I'm concerned about rebuild times (it's a pool of 4 22TB drives). Is btrfs a better choice for this use case, or should I just go with raidz like I originally planned?

Edit: I should have mentioned that I already have 4-3-2 backups configured - I'm primarily interested in the "self-healing" aspect of ZFS so that I don't have to recover from backups unless necessary, and to resolve corruption on the fly without me having to notice that a file is corrupt.

If you haven't seen it yet, we recently made the announcement that starting July 1, 2026, the price of "Jellyfin Premium+ One Super Unlimited (with Ads)" will increase to $0.00 USD*. There has been a lot of enthusiasm regarding charge backs, and we're simply blown away by the community's response.

As we've had a high volume of inquiries, I'd ask if you could please wait until I'm off the support email shift to reach out about this issue. I've attached our schedule so you'll know when it is safe to reach out.

Thanks, and happy streaming!

*Example price in USD. Exact pricing in other currencies may vary.