Hi, I'm the author of GPT-Load, an MIT-licensed AI gateway with 7,000+ GitHub stars.

It manages API keys and supported subscription accounts in one place. Your clients connect through the gateway, which handles credential scheduling, automatic failover, access controls, request logs, and usage tracking.

It runs with Docker Compose or as a single Go binary, includes a web UI, and uses SQLite by default. You don't need a separate database to get started.

One feature I'd particularly like feedback on is reversible request redaction.

Configurable regex rules replace or encrypt matching text locally before it reaches an upstream service. If the model returns intact, valid ciphertext, GPT-Load can restore the original values in response text and client-side tool arguments.

For example, an email address can be encrypted before reaching the model, then restored when the model includes that ciphertext in a tool call returned to your client. The rules apply to supported text fields; image and file contents aren't covered.

There's also an optional, experimental JEV guardrails integration. It reviews outgoing text against custom rules and can warn or block on matches. It uses an external review service, is disabled by default, and failed or incomplete reviews may still allow requests through.

You host the gateway, not the cloud models behind it. Cloud providers still receive the processed requests, and you need your own upstream access.

GitHub: https://github.com/tbphp/gpt-load

Docs: https://www.gpt-load.com

I'd appreciate feedback on the Docker setup and how reversible redaction behaves with the clients you use.

AI disclosure: AI helped draft this post.

Hi, I have the following specs:
110 Gigabytes of DDR4 RAM
Two intel Xeon E5-2630 V4

No dedicated GPU, but fastfetch shows a nVidia geforce 210 discrete GPU.

My goal in this project is to be able to run a modal equivalent or slightly better than gemini 3.8 flash, this is the only model I use currently for coding so if I am able to replace it with something local that would be great for having governance over my tools.

Since this model will be used for coding only, logically a dedicated GPU wouldn't be needed. but this is my first time learning about this so I could be wrong.

Hi everyone,

For the ones who followed along: 640 stars now, up from 100 when I first posted here. Still the same messy solo side project, but v1.0 changed what it can do.

The short version of why it exists: I keep losing the thread when I walk away from a project. Notes in one app, configs in another, no big picture. So I built a canvas where all of it connects. That part you know.

What's new in v1.0 is the part I'm proudest of: the canvas is now a Git artifact. A project syncs to a repo, structure, notes and block positions version-controlled inside a .ideon/ directory with checksums. The rest of your repo stays untouched. You edit the canvas, you push, and the history sits in Git like code. Diffs, reviews, rollback. Not my cloud, your repo.

Also in 1.0: database block with typed columns, mermaid with live rendering, and a chained audit trail so every state change is traceable.

What's next: a plugin API so people can build their own block types, and a desktop app once the project grows enough to justify it.

The long-term idea is the canvas stopping being a map and becoming a system. A graph that remembers everything and eventually reacts on its own, (from just blocks to neurons 👀).

Still two containers, app + Postgres, one docker-compose up

Repo: https://github.com/3xpyth0n/ideon

Hope it's useful for your own labs :D

I’ve been working on building my own personal AI assistant for a while now, and I’ve been wondering what other people actually want out of theirs.

There’s ChatGPT, Claude, Alexa, Siri, Home Assistant, and a bunch of other options, but I feel like there’s still a pretty big gap between what these things can do and what I’d actually want them to do.

I’m curious what everyone else’s experience has been like.

* What’s something you’ve wanted to automate but haven’t been able to?
* What have you tried, and why didn’t it work?
* How important is running things locally to you? Would you sacrifice some performance for privacy?
* What’s something you wish your current assistant could handle without you having to walk it through every step?

I’d also like to hear from people who are happy with their current setups and what they’re using

Basically the title.

I’ve set up Mealie, Plex (and Plexamp), a family planner (weekly meals, budget, calendar, etc.), and more.

She discovered a fantastic family planning app that we started using yesterday. However, after reading about the data it collects, I was quite concerned. It gathers our addresses, emails, check-in notes, menstrual cycles, full calendar access, and more. I found a self-hosted alternative that looked very similar to the app she found, explained it to her, and demonstrated how it worked when I set it up.

This led to a conversation that eventually turned into an argument about privacy and accessibility. I am very privacy-oriented, while she essentially says, “I don’t care about sharing personal details with company X; let them see when I have my menstrual cycle, etc.” She mentioned that the family planning app she found looked better and “warmer” and preferred it over the self-hosted one, even though they are essentially the same. To me, it’s baffling that she chooses minor UI details over our privacy.

Any tips on how to persuade her to take her privacy more seriously? Is all hope lost?

didn’t realize it was this kind of subreddit, but since I do have something I’ll share. glad to find a place to show off!

utilizes the built in Minecraft server RCON protocol to act on behalf of logged in users. prioritizes parity with vanilla files over everything.

Dev here. ScreenTinker is a self-hostable signage CMS (Node/Express/SQLite, MIT, Docker image on ghcr). v3.0 is out:

• Guided first run + Simple view for new users; import from Xibo, Yodeck, ScreenCloud and others.
• Content requests - an approval-gated link so people without an account can send content for the screens.
• Screen share (peer-to-peer WebRTC, TURN supported with short-lived credentials) to several screens at once.
• Blank/frozen screen detection, stale-content and accessibility checks, captions via a local Whisper server.
• Private A.I. - point it at your own Ollama/OpenAI-compatible box; a Data & privacy page lists exactly what leaves the server.
• Passkeys, SCIM, full data export, and moving an org to another server by import.

• Every install now ships its player packages: upgrade.sh fetches the signed APK etc. (checksum-verified), and the Docker image builds the native Pi player.

  Upgrade notes: Node 22.14+ is now enforced, and the first start snapshots the DB. From a 2.6 git install, run 3.0's upgrade script (the command is in the release notes) - we hit an apt needrestart race on our own prod upgrade, so the notes include the fix.

  Thanks to gainskills and arminfauland for PRs.

  How A.I. is used: most of the code is written with Claude Code, and I'm not going to pretend otherwise. I've been doing IT/telecom/security for 20+ years (network architecture, firmware RE, hardware hacking), so my job on this is the stuff AI is bad at: architecture, threat modelling, reviewing what it writes, and testing on real hardware (Fire TV, Android, Tizen, webOS, Pi, BrightSign, Roku). Nothing reaches production without my sign-off, and community bug reports from people running real screens drive a lot of the fixes. This post was drafted with Claude and edited by me.

  The A.I. features in the product (sign suggestions, translations, captions) are optional and off unless you configure a provider. Point them at your own hardware and nothing leaves your network.

  MIT licensed, all the code is public - judge it on that.

https://github.com/screentinker/screentinker

Hi folks,

I've been working on Zync, a desktop SSH workspace for Windows, macOS and Linux.

Website: https://zync.thesudoer.in
GitHub: https://github.com/zync-sh/zync

Zync is built for the everyday work of connecting to servers, checking logs, and moving files, without constantly switching tools:

• Terminal, SFTP browser, and port forwarding in one window
• Credentials stored locally in an encrypted vault, no account, no cloud sync
• Local shells and remote SSH sessions share the same workspace
• Jump hosts, SSH config import, and visual port forwarding (local, remote, SOCKS)
• Snippets, command palette, and session restore, pick up where you left off
• Optional encrypted backup to your own Google Drive
• A plugin marketplace for themes and plugins
• Runs fully on your desktop, light on resources

Recent update (v2.35.1): make the workspace your own:

• Custom color themes, including import/export of theme JSON files
• Renameable tabs and dockable panes
• A side navigation bar you can toggle
• Keyboard shortcuts are easier to discover and edit, including bindings that work while the terminal is focused

Update in action: https://pub-f5d307b0347348988dccc997da10756a.r2.dev/2.35.1.mp4

Release notes: https://github.com/zync-sh/zync/releases/tag/v2.35.1

One transparency note: AI tools helped write parts of the code, but all design decisions, architecture, and code reviews go through me.

Would love feedback, especially from folks managing a bunch of homelab boxes.

Basically the title.

There are plenty of these apps on the AppStore that are pretty great. But they all have the same issue. I’m not controlling the data and they usually cost money.

I.e an app that:

* Has date scheduling

* Todo lists

* Long term todo

* What to buy

* Mealplanning/grocery list

* Can be shared between users. I.e updates on my end reflect on the partners end

* etc.

I hope I’m asking the right questions, and that you understand what I’m after.

Hi everyone. On my home lab (Proxmox) I am running Caddy reverse proxy with ACME certificates for internal services. Right now the only open port on the OPNsense firewall is for WireGuard.

I would like to also expose my Jellyfin instance to a friend (for a hassle-free use on LG OLED TV), but keep it as secure as possible without getting a separate VPS. Jellyfin now is on a trusted VLAN (but not on a management VLAN).

My current ideas are as follows:

1. Expose uncommon TCP port to the internet, and whitelist my friends IP address
2. Setup Caddy so that it also does IP address filtering of friend's IP
3. Friend would simply enter my custom domain+port to connect

Some questions:

• Would it add to security to run a separate Caddy instance on a isolated VM just for this purpose? (as opposed to exposing my main Caddy instance which is server my whole internal network)
• Currently my Jellyfin is running on unprivileged LXC as systemd service, would this be good enough, or shall I get a separate hardened Jellyfin instance in an off-chance that it would get hacked.

Any other ideas to harden this further?

Hey there,

first of all:

Kuvasz is an open-source, self-hostable monitoring solution (HTTP, TCP, DNS, push, Docker and ICMP) with status pages, webhooks, an MCP server and IAC support, a great alternative to UptimeRobot or Kuma.

How AI was used in the project: I started working on it in 2020 and I didn't use any LLM up until this May (version 3.8.0). Since then I use Claude Code in a quite "old-fashioned" way: I commit everything by hand after carefully reviewing every change on the project. The pre-existing quality gates of the project are also very strict to make slop even harder to introduce.

I was working on the latest release a lot, probably this is the biggest one since the project exists:
https://kuvasz-uptime.dev/changelog/#4.5.0

A brand new dashboard (see the screenshot above)

The old one was quite ugly and also not so informative, so I rewrote it from scratch.

Docker monitoring

Instead of checking a port, Docker monitors ask the daemon whether a container is actually running and healthy. They catch crash loops, OOM kills, paused containers and failing healthchecks, and the errors say what happened, e.g. "The container exited (137) after it was OOM killed". Restart counts and CPU/memory history are recorded too. The daemon can be local, behind a socket proxy, or remote over mTLS.

Slack Bot integration with threading support

Every incident and maintenance window gets its own thread, so a flapping monitor no longer floods the channel. The first message always shows the current state (updated after a resolution) and details + notes are sent to the thread.

Incidents, properly told

Each incident has a details page with a timeline: when it started, who was notified, the notes you added, and when it was resolved. Public notes also show up on status pages, next to the active and recently resolved incidents.

Also in this release:

• Configurable color schemes for the app and the status pages
• HTTP and TCP checks through HTTP or SOCKS5 proxies
• An opt-in connectivity check that pauses monitoring while the Kuvasz host itself is offline, so you don't get an incident storm
• An interactive install script for Docker Compose
• PostgreSQL over a unix socket, a more locked-down Helm chart, and a fix for shutdowns hanging while checks were failing

Live demo: https://demo.kuvasz-uptime.dev (user: demo | pass: secureDemoPassword)

GitHub: https://github.com/kuvasz-uptime/kuvasz

I've been collecting books, games, and movies long enough to have watched the shelves change several times.

Physical books became ebooks. Game cartridges gave way to digital collections. Movies went from videotapes to DVDs, then Blu-rays, and eventually files on a drive. Comics made that journey too.

I like the convenience of digital media. But over the years, my collection ended up spread across folders and different tools. I could still find things, but it didn't quite feel like one collection anymore.

That's why I started building FolioSpace Library. I'm its developer, but I'm also the person using it to organize my own stuff.

It's an open-source, self-hosted library that runs with Docker on your own computer or a compatible NAS. It brings books, comics, and game collections into one place. I've recently added movie poster fetching through TMDB, so the film collection is starting to feel more like a shelf I can browse, too.

For the game-library side, I took inspiration from the open-source RomM project. A big thank-you to the RomM team and contributors for their work. It helped shape how I approached this part of FolioSpace Library.

What I enjoy most is a fairly ordinary thing: opening one place and seeing the things I've collected over the years. A book, a game, a film. Different formats, but all part of the same personal library.

There's something reassuring about that. The formats have changed, but the collection still feels like mine, and I can keep organizing it on a system I control.

I'd love to hear from others who've made the same journey. Do you prefer separate tools for each kind of media, or would you like a shared home for the whole collection?

GitHub: https://github.com/funland/foliospace-Library
Website: https://foliospace.app/

to clear things up: the point was to check whether an uncensored qwen3.8-27b in atomic agent acting as orchestrator could get a cloud model past its own guardrails. the bot farm was just the setup i picked for that test.

i was paying $340/month to test buffer, hootsuite and a va to manage 8 twitter accounts. and then i built the thing myself, not a saas replacement exactly more like a small infrastructure project that happens to post tweets.

what's running:

• macbook pro m5 (32gb) at home, always on. runs llama.cpp with qwen3.8-27b-instruct-uncensored-v2 (q4_k_m gguf, ~15gb). this is the brain: reads config, schedules, scores output.
• 4× hetzner cx22 ($5 each = $19/mo total). these are just ip rotation targets. round-robin swap in cron so no single ip does all the posting. each one gets a playwright headless chromium instance when it's its turn.
• sqlite database per account batch. logs every action: what was posted, when, which proxy, score from the model, whether it got rate-limited.
• proton mail api for generating signup emails. sms-activate for phone verification ($0.7/number).
• claude opus via openrouter as the writing engine. the local model decides WHAT to say and WHETHER it's good enough; opus just writes it fast. costs about $4/month at this volume.

total self-hosted cost: $23/month versus $340 before, the laptop was already mine so that's sunk cost.

the scheduling is a single cron line:

0 6,10,14,18,22 * * * python3 ~/farm/orchestrator.py --batch >> ~/farm/logs/cron.log 2>&1

fires 5 times a day, each run takes ~20 minutes, the orchestrator reads farm.yaml (37 account entries with personas, schedules, niches), figures out who's due, spawns parallel workers for each, collects results, scores them 1-5, queues anything under 3 for my daily review.

account creation was a one-time thing but it was the annoying part. wrote a playwright script that does the full signup flow: random proton email → fill form from persona yaml → wait for sms code via webhook → submit → handle captcha if it appears. capped at 12 accounts/day/ip to avoid datacenter-burst patterns. three days of running it overnight gave me 37 handles. i solved two captchas on my phone while eating cereal. avatars are random unsplash crops which is peak "real person" energy.

each account per day does:

• 2-4 tweets
• 15-25 likes/rt spread across batch slots with random 30-90s delays between actions
• 3-5 comments on trending threads in its niche
• if one of their own tweets gets >10 replies within an hour, worker goes back and drops 2-3 follow-up comments

the vps rotation is the part that keeps it from looking like one ip doing everything. cron picks the next hetzner box round-robin, sets the proxy env var, launches chromium against it. if one box gets rate-limited the script backs off 90s and retries on the same box; second failure rotates to the next one. haven't had a full outage yet but the log shows about 3-4 rate_limit events per week across all accounts combined.

numbers after 14 days:

the whole thing is a yaml config, a python script (~400 lines), sqlite, and one cron entry. no docker, no k8s, no orchestration framework. if your macbook can hold a 15gb gguf in ram you can probably do this too. the hetzner boxes are doing almost nothing except being ip addresses with chromium installed.

My box was fine for like a year. Vaultwarden, Uptime Kuma, Paperless and a couple of small Node things, all in Docker on a 4GB VPS. As soon as I added Immich last weekend, my machine started swapping hard the second the ML container kicked in. Load average hit 9 and Vaultwarden timed out on my phone.

I know Immich is the hungry one but now I'm wondering if I just undersized everything.

What does your stack actually sit at in docker stats? Do you split the heavy stuff onto its own box or just buy more RAM? Is anyone running Immich ML on a VPS at all, or is that a home server job?

Kinda annoyed I didn't check this before uploading 40GB of photos.

Recently (the last 2 days), I have been having a major problem with Grimmory not adding the new books/audio that I add to the library. With a lot of persistence, I have to use the CLI to log in to MariaDB to remove the delete record(s) that cause it to hang, and it is a real PITA to try to do from the CLI. I seem to recall seeing a program not too long ago that interfaces with the databases, but I do not recall the name, or if it was what I am thinking it was. Is there such a program or a better method for accomplishing what I need to do? It is not just MariaDB; it is other types of databases as well.

I'm an engineer at Mulga, and we build Spinifex, an AGPL-3.0, self-hosted platform that serves the AWS APIs on hardware you own. You point the AWS CLI, an SDK or the hashicorp/aws Terraform provider at your own endpoint and get real resources: aws ec2 run-instances boots a VM on your hardware, and terraform apply builds a VPC on your network. Emulators like Floci and LocalStack mock the APIs for testing, while Spinifex runs the infrastructure your workloads use.

What it's for

• Move compute-heavy AWS workloads such as GPU inference onto your own hardware, without rewriting the code or the Terraform.
• Self-host software that was built for AWS, including on an air-gapped network.
• Learn AWS without a bill: build the VPC, EC2 and RDS stack from a cert course and leave it running for a month.
• Keep one AWS profile for work and another for the rack in the cupboard, with the same commands for both.

Running it

Install a single node onto an existing Ubuntu 26.04 or Debian 13 machine using the binary installer https://docs.mulgadc.com/docs/install or do a fresh install using a bootable USB https://docs.mulgadc.com/docs/install-usb

Repo: https://github.com/mulgadc/spinifex

Started using a Docker Manager (Arcane) with built-in vulnerability scanning (using Trivy) which is also able to automatically patch docker images (using Copacetic/Copa). I'm frankly astounded at the number of vulnerabilities it found in just the small handful of containers I'm running. The worst offenders are Immich, with 745 vulnerabilities spread across 4 containers, and Nginx Proxy Manager with a staggering 1,420 vulnerabilities.

I tried patching a couple non-essential containers (iSponsorBlock and Scrutiny) just to familiarize myself with the process in case I broke anything. It's manageable, albeit a little cumbersome. But I'm scared to try patching system critical things like NPM and Immich, for fear of breaking things.

I'm just surprised that this isn't talked about more. Are people just out here raw-dogging their docker images and that's normal? Or is this a non-issue and I'm worrying about nothing?

Hi everyone!

I'm working on an internal project for our company, and I'm looking for recommendations on existing open-source tools or implementation approaches.

Our goal is to build a task management system where managers can easily see what everyone is working on, track progress, and identify overdue or blocked tasks.

Key requirements:

• Managers need a dashboard showing tasks assigned to each employee, current status, progress, and deadlines.
• Employees should be able to update their progress and report blockers.
• The system should automatically send reminders before deadlines, when tasks become overdue, or when progress hasn't been updated for a while.
• Ideally, reminders should be delivered through WeCom (WeChat Work) or Lark (Feishu), since these are commonly used in our workplace.
• Self-hosting and customization would be a big plus.

I'm considering building this ourselves, but I'd prefer to start from an existing open-source project rather than reinventing everything.

I've looked into Plane, OpenProject, and workflow automation tools like n8n.

My questions:

1. Are there any open-source projects you'd recommend for this use case?
2. Has anyone integrated a task management system with WeCom or Lark?
3. Would you recommend customizing an existing platform or building a lightweight system from scratch?
4. Are there better architectures or tools I should consider?

I'd really appreciate any suggestions, GitHub repositories, or real-world implementation examples.

Thanks!

I am new to new hosting stuff, i am trying to get my personal ai assistant to send me a message every morning of my emails , meetings , tasks etc.

So the claude suggest me ntfy i checked it and found out that ntfy is open source. I got an idea to make it super secure why not self host it by downloading the docker image and host it on Render or any other free plaforms?

Is this a good idea? Is anyone using like this? Never used ntfy in my life

Tailscale back to my own machine works until the power drops or i am on a bad connection. A VPS seemed cleaner. I wanted it up whether or not the laptop was. I started from price. The cheapest VPS for Claude Code that I could find was about $6 a month. On paper that was the whole answer. In 30 days I still had 3 mornings where it was just down, about 40 minutes each before it was usable. I have also read that some cheap provider IP ranges get blocked, so the $6 box may not even be allowed to sign in.

If you actually run Claude Code on a VPS, which provider stayed up and did not get blocked? I care more about the one that still worked on day 30 than the lowest sticker price.

GitHub: https://github.com/Leonetienne/Comaney

Web: https://comaney.app

I've been working on and using/polishing Comaney for over half a year. It's finally polished enough that I want to share it.

The goal is to get useful insights into your spending habits without making bookkeeping a chore.

Comaney helps you track where your money goes, manage individual budgets (like keeping Amazon spending under control), and see how much you have left to spend this month.

Some things I find particularly useful:

• Shared expenses: Use it with your partner, roommates, or a group of friends on vacation. Comaney tracks who paid for what and calculates who owes whom. Not every expense has to be shared with everyone equally!
• Project aggregation: Group expenses into projects such that you know how expensive that house renovation was all-in-all.
• No account needed for everyone: Add offline users you manage yourself and convert them to regular accounts whenever you want.
• Optional AI bookkeeping: Don't want to fill forms by hand? Describe a purchase or take a picture of a receipt. AI handles the entry for you, including breaking it up to better fit tags / categories. It can even create custom dashboard widgets.
• Your AI, your choice: IF you want to use AI: Use local models via Ollama or llama.cpp, or connect providers like Claude and DeepSeek.
• Custom dashboards: Build your own views, customize the appearance, and track what matters to you. You can even add a custom wallpaper.
• Automation: A REST API and MCP server let you integrate Comaney into your own workflows.
• Your data stays yours: Self-host it and export everything whenever you want.

Comaney is designed for self-hosting, but there's also a public instance with a demo login and a small AI usage budget: https://comaney.app

I'd love to hear what you think, especially if you end up using it!

Why not use an existing project? I have tried using firefly III and actualbudget. Both did not solve my problem at all. Firefly being two full time jobs to maintain and AB being very insufficient regarding the insights it provides.

The workflow using to bring this to life is to have an experienced developer working in the field since long before ai (me) using classic agile development workflows accelerated by ai agents. This way of development does not sacrifice quality but enables me to produce this service by myself next to my full time job.

According to this email from today, it looks like we're in for another round of .com price increases effective Nov. 1. Pretty sure our renewals were $16.88 not too long ago. Looks like we may be seeing the continued impact of wholesale price increases. At this point we're getting into GoDaddy markup ranges :( Not sure what the situation will be for premium TLDs. Should we view this as reasonable? Looks like a potential open ended problem.

Sup,

Is something like this possible in a secure way? Is there reliable enough, already made software out there to achieve this? Would you recommend this path, or do you have a better idea?

Background / Resoning:

I currently use Tailscale to connect to my services, but I can't share my pictures this way with friends or family. A Cloudflare tunnel is also not ideal, since all the media would need to be streamed through them (usage limits and privacy). Finally, I don't want to expose any part of my LAN publicly, since my router didn't get updates in 5y and I don't know enough, except blocking all incoming traffic is pretty safe.

I got a raspberry left over and own a domain. I would place the Raspberry in front of my LAN.

Hi r/selfhosted,

It’s been a while since our last post, but since then a lot of new features have been added to Dreeve.

Dreeve is a self-hosted, open-source dashboard for your sports and fitness data

Features and improvements worth mentioning since we lasted posted here:

• Released an API spec: https://docs.dreeve.app/api/
• Added several connectors to automatically sync activities from external platforms: https://github.com/orgs/dreeveapp/repositories
• Added automation rules to streamline gear tracking, commuting flags, and more
• Added support for managing custom segments
• Added explorer tiles to the heatmap
• Multiple new dashboard widgets
• Integrated WindAhead with Dreeve segments

As always, thanks for your feedback and I'm looking forward to more feature requests!
Stay fit, stay healthy 💪

• Example: https://demo.dreeve.app/dashboard
• GitHub: https://github.com/dreeveapp/dreeve
• Docs: https://docs.dreeve.app/#/

I am trying to get pterodactyl setup on my server but cannot get past setting up the actual node. I'm having issues with the remote url, if I put in my subdomain it sends a 302 html response instead of the expected json response. If i try to put in localhost I can get the "tls: failed to verify certificate | doesnt contain any IP SANs". I followed the pterodactyl documentation but could't get letsencrypt to work with cloudflare, so I found this tutorial which sets up the certs with openssl. I do not know what I am doing wrong at this point and would appreciate any guides on how to set up pterodactyl with cloudflare.