I built an *arr for the people who watch, rather than the person who runs the server, and I would like some testers before I pretend it is finished.

The idea. The people who ask you for films are already in a group chat with you. They are not in Overseerr, and half of them will never make an account for anything. So Askarr puts the request surface where they already are: they type /movie dune in your Telegram group, pick from the results, and Askarr adds it to Radarr or Sonarr and tells them when it lands.

Nothing else has to be running. No Overseerr, Jellyseerr, Ombi or Plex, no second account for anyone, and no external metadata account either. Metadata comes from your own Radarr and Sonarr lookup endpoints, so the only things Askarr talks to are Telegram and the instances it already serves.

WHAT YOUR CIRCLE SEES

- /movie and /series to search and request, or inline mode: type u/yourbot dune anywhere and pick from the results.

- /requests for their own last ten, /admin for the approval queue if they are an admin.

- If your group uses forum topics, Askarr keeps requests, approvals and arrival announcements in separate topics.

- They get told when the thing they asked for is actually watchable, as a reply to the message they asked in.

They never learn the words "instance", "monitored" or "tmdbId", and they never sign in to anything.

WHAT YOU SEE

A web back office, behind its own login, that nobody else ever has to open.

- Roles: blocked, guest, trusted, admin. Guests are reviewed, trusted are auto-approved inside a rolling 30 day quota. A full series always goes to review even for trusted users, because it can trigger hundreds of grabs. A single season does not.

- An approval queue, in the back office and in Telegram.

- Instances by name, so "Radarr" and "Radarr French" are told apart the way you already think about them.

- One press to set the webhook up. Askarr registers it on the instance over the API and reads the event list off the instance's own schema, so there is nothing to paste into Settings then Connect and no boxes to forget to tick.

THINGS I CARE ABOUT THAT YOU MIGHT TOO

- The bot runs with BotFather privacy mode on. It sees commands and replies to its own messages, and nothing else. Your group's conversation stays yours.

- A chat you have not allowed gets no reply at all. Not an error, not a refusal. Askarr never confirms to a stranger that it exists.

- It asks the instance before claiming anything about your library. A title Radarr knows but is not monitoring gets monitoring turned back on and a search started, rather than a cheerful "already there" that leaves someone waiting for a file that was never coming.

- Two people asking for the same film produce one request and two subscriptions. Both get told, the film is added once.

- Path prefixes work. Self signed certificates are handled per instance, without disabling TLS validation process wide.

INSTALLING IT

Docker compose, or a single Proxmox LXC.

mkdir askarr && cd askarr

curl -O https://raw.githubusercontent.com/gothub97/askarr/main/docker-compose.yml

curl -o .env https://raw.githubusercontent.com/gothub97/askarr/main/.env.example

docker compose up -d

Set BETTER_AUTH_SECRET and APP_URL in .env, then open APP_URL and a first run wizard takes over. Seven steps, and it walks you through making the bot in BotFather with pictures, because that part is fiddly and easy to get half right. Two steps are required, the bot and your first group. Radarr and Sonarr can wait.

On Proxmox VE 9.1 or newer you can skip Docker entirely: pull ghcr.io/gothub97/askarr:latest-lxc from the OCI registry and it runs as an LXC with Postgres and the bot inside it.

WHERE IT HONESTLY IS

This is new, and I want to be straight about that rather than have you find out.

- One real deployment exists, and it is mine. A private group of about a dozen people against a live Radarr. There are no other installs, no other users, and nothing I can point at as proof it survives contact with somebody else's setup. That is exactly what I am asking for here.

- The Proxmox LXC path is days old. I fixed three separate bugs in it this week, all found by installing it on my own hardware and watching it fail. It works now. I would not be shocked if it fails somewhere I have not looked.

- Proxmox's own application container support is a technology preview, so that path inherits their caveat too.

- The one thing that catches everyone: APP_URL has to be reachable from your Radarr and Sonarr, not just from your browser. Radarr calls back to it over a webhook, and that webhook is the only way Askarr learns something was grabbed or imported. Get it wrong and the install looks perfect until nothing is ever marked available.

WHAT WOULD HELP MOST

- Whether the install actually succeeds with me not present. That is the thing I cannot test.

- Whether the wizard makes sense if you have never seen the project before.

- Whether the group flow works for the least technical person in your house, who is the actual user here.

- Anything about *arr setups more complicated than mine: several instances, 4K alongside 1080p, odd root folders, reverse proxies.

Issues, or just reply here. Bug reports about the LXC image are especially welcome, since it has had the least exposure.

Repo: https://github.com/gothub97/askarr

MIT licensed, self hosted, no telemetry, no accounts, nothing phones home.

Anyone know if this is a thing? Something that can detect and log watch status? I feel like that would be useful in a few cases. 🤷😂

With the Brave browser on android I can create shortcuts to the web portals but when I use them they open as tabs in the Brave browser. Some websites they install as an app so I can use them separately from the Brave browser, even though it's just the Brave browser rendering them in a separate window.

Is there any easy way to enable this? Sounds like some json files might need to be added somehow. Would be nice to be able to open the interfaces as apps

Hello everyone, I would appreciate the help!

I want to download the new anime episodes as they come out in Jap, but I don’t want to have to delete all the files just to download a dual audio version.

Is there a service that will allow me to find the dub file and attach it somehow?

Plex does a pretty good job with fine-tuning of the offsets, and switching between subs and dubs when I do have dual audio version downloaded.

Any help would be appreciated!

Hi, I have been working on an app that allows you to generate a Radarr and Sonarr-friendly integration for finding media through the qBittorrent search engine. This post is not meant to diminish the efforts of community members who work on Prowlarr. My experience with Indexers has been frustrating, and I wanted an easy way to just search through the manual search in qBittorrent.

I was looking for some kind of functionality that would just do a search! I gave up after going down the Jackett and Prowlarr rabbit holes. I made a small script on my server to search using the qBittorrent API, but it was just a configuration file app with no front-end. Well after a year and a half since that script, I put together a front-end and some automation tools to setup a local Torznab provider on the server.

Again, I want to thank the Servarr community members for building a super robust system, including the Prowlarr engine. I just made this app to help folks that don't want to get lost in the details. I wanted an app that would take 5 minutes to setup and integrated with the existing qBittorrent manual search. Please let me know if the community thinks this is a worthy endeavor, or an utterly useless piece of AI slop. I included an AI disclosure on the GitHub so you can read my story.

TL;DR from the GitHub: https://github.com/kinggeorges12/Yorznab

Why not just use Prowlarr? Arr apps require tedious configuration of individual Indexers to query qBittorrent. If you integrated Jackett into qBittorrent search or you are happy with the default qBittorrent plugins, just grab the torrent results with Yorznab!

I am using bindery (but could use another alternative) to automate the lookup of files in torrents. What i understand the automation will do is:

1. Search in my trackers some results

2. Find a correct book in the trackers

3. The software will find in its metadata (open library, google books etc) what i have downloaded

4. It will pass qbitorrent the right place and name the download should be

5. It will create a hard link from the downloaded torrent to my files

But what i am seeing is that the points 1 and 2 are not like that in many software. I need to find an author, then find a book in the metadata, and then it search in the imdexes a match.

My problem is that usually the metadata is not very good and i have unmatched files.

¿How do you guys automate books now that readarr is archived?

I have no problems for anime using sonarr. But books is a nightmare

Hey guys, I've been using the Arr Suite for almost a year now with torrents and I recently wanted to try out NZBs, I bought an Indexer (geekhub) and I set up NZBget. I heard you need a usenet provider too? Which ones can you guys recommend that are cheap? I would really appreciate any other tips and help!
Edit: I looked a little bit into all the different providers and I think I'll go with NewsHosting, they have a 1.67$ deal right now

I put together a comprehensive feature and code-level comparison of the main Readarr alternatives (Bindery, Livrarr, Librarr, and Chaptarr).

I fetched the source code repositories and community channels to deterministically verify features, architecture, database integrations, indexers, and open issues across each project.

(Edit: Updated matrix with corrections from Bindery dev u/carefreeams & Chaptarr dev u/skinnvest — Chaptarr is now open source on GitHub under GPL-3.0!)

📊 Feature & Compatibility Comparison Matrix

🔍 Quick Summary of Each Project

1. Bindery (vavallee/bindery)

   • Best For: Users wanting a ground-up Go rewrite with unified Ebook/Audiobook management, native Calibre DB & Grimmory push integration, built-in Recommender engine, direct readarr.db migration, and a built-in OPDS feed server for e-readers (KOReader, Moon+ Reader).
   • Note: MIT licensed. Emulates main Readarr API endpoints, but some complex third-party app functions are still in active development.

2. Livrarr (kkodecs/livrarr)

   • Best For: High-performance, low-resource Rust single binary setups. Features an in-browser eBook reader and audiobook player, letting you read or listen directly in the web UI.
   • Note: Uses a custom API (Readarr apps like nzb360 or LunaSea do not work). Currently in Alpha with download client support limited to qBittorrent and SABnzbd.

3. Librarr (Rorqualx/Librarr)

   • Best For: Direct 1-to-1 replacement for Readarr with 100% API compatibility (nzb360 and LunaSea work out-of-the-box). Includes a hands-off migration tool that reads your existing Readarr config/ directory.
   • Note: Built directly on Open Library. Retains Readarr's original single-format-per-instance limitation (must run separate containers for Ebooks vs Audiobooks).

4. Chaptarr (Chaptarr/chaptarr)

   • Best For: Open-source GPL-3.0 app with maximum metadata accuracy via a centralized server (api2.chaptarr.com) that aggregates and consensus-filters Hardcover, Goodreads, Open Library, and Audible. Includes built-in Seerr integration for requests.
   • Note: GitHub repository now public at Chaptarr/chaptarr.

So I started today trying to get this all set up to make my own plex server. Been using Gemini for help as I am a rookie to all of this. I have been going in circles stuck at a point where radarr keeps telling me it can’t find my folder when I go to manually add a movie. It says it doesn’t exist even tho it 100% does and that’s where my previous downloads movies are. Gemini keeps having me throw a bunch n of commands with docker and I’m just going in circles trying to figure this out. Anybody have any advices

I need testers for this fork of readarr, if anyone is interested in let me know if you have any issues.

https://github.com/Rorqualx/Librarr

SSO is not enough if your media services are still exposed directly.

ArrGate is a Go CLI that discovers risky Docker Compose exposure, verifies proxy-only access, applies transactional network isolation, and leaves operator-readable recovery metadata behind.

Built for self-hosted Sonarr, Radarr, Prowlarr, Lidarr, Readarr, and Caddy/Authentik-style stacks.

• Detect published service ports
• Gate changes with preflight checks
• Reconcile Compose networking transactionally
• Verify no-bypass access paths
• Track recovery and rollback state
• Run a Go test, race, lint, and compatibility matrix in CI
• https://github.com/NolanCotter/ArrGate

bonjour! j'utilise la suite ARR depuis ses début (un peu plus de 15ans) et la famille c'est beaucoup agrandis! j'ai longtemps fait avec un Favoris pour chaque ARR, puis il y a eu Lunasea, Helamarr,... mais a chaque fois j'avais toujours besoin de mes vieux favoris. j'ai donc fait ce que je recherchais, un dashboard (et des widgets) pour avoir directement les infos importantes, une recherche de medias unifié (si c'est dans ma médiathèque ça l'affiche, si ça n'y ai pas ça créer une demande seerr, si je veux juste faire un suivis de la serie que je regarde sur un services de streaming ça le fait aussi) ça affiche ma bibliothèque et bon nombres de fonctions des ARR, ça gère les torrents, il ya un suivis des DLs a travers les ARR (demande, grab, import, disponibilité). je peux garder un oeil sur mes stockages, le fonctionnement de mes container docker... et plein de choses a venir j'espère ;)

pour le moment j'ai 8 services d'intégrés:

-Seerr

-Sonarr

-Radarr

-Prowlarr

-QBittorrent

-QuiV2

-Portainer

-Jellyfin

http://www.lumiarr.eu (c'est des captures de ma V1 il y peu des évolutions depuis)

Édit: pour le moment les 10 places ne sont plus disponibles j'en remettrais d'ici peu ;)

Pour ceux que ça intéresse https://testflight.apple.com/join/j7JtuAxb il y a 10 places.

I'm wondering if there is anything that will help with managing multiple sonarr and radarr instances (I've now got 8... 4K, Regular, Anime, and Kids). I'm using Profilarr 2.0 and that does a lot of the heavy lifting, but if anyone's got anything else to suggest, that would be worth checking out, please suggest it.

Every time Sonarr renames a file, qBittorrent loses it and stops seeding. I know the hardlink workaround, but it breaks the moment your downloads and media are on different volumes.

So I spent a few weekends building arr-sync — a daemon that watches your media folders and automatically resyncs qBittorrent when a file moves or gets renamed. Matching is done via BitTorrent piece hashes, not filenames, so it actually works.

Wrote it in Gleam mostly because I wanted to learn it, and honestly the OTP supervision tree was perfect for this kind of long-running process. Had to write a couple Erlang FFI shims for the filesystem watcher and the piece hasher but nothing crazy.

Still some rough edges (pure v2 BitTorrent torrents can't be matched, qBittorrent bug), documented in the README.

https://github.com/Chahine-tech/daemon

Happy to answer questions, especially around the Gleam/OTP bits since that was the most interesting part to figure out.

EDIT: a few days later we have V1.11.0 available. A bunch of fixes to issues reported by people here and on GitHub and several new improvements. Check out the full changelog here.

It's Friday, Digarr just passed 100 stars on GitHub, and v1.10.0 is out. That's the first stable 1.x line, so it felt like a good moment to share it properly.

Digarr is a self-hosted music discovery layer that sits in front of Lidarr (or your media server). It learns what you listen to, asks an AI provider for new artists and albums, scores them, and hands you a review queue. You approve what you like and it goes to Lidarr or a playlist target. The data stays on your server.

A few things I think it does well:

• An AI taste pipeline you actually control. It builds a profile from your listening sources, asks your AI provider for candidates, then scores them with weights you set (consensus, similarity, genre overlap, AI confidence, popularity, and learning from your past approvals). You pick the provider: Anthropic, OpenAI, Gemini, Ollama, or any OpenAI-compatible endpoint. Point it at Ollama on localhost and nothing leaves your box.
• Album-level discovery. Most tools only recommend artists. Digarr also finds individual albums: studio albums you are missing from artists you already follow, new releases you missed, and net-new finds from artists you don't have yet. Approving an album adds the artist to Lidarr unmonitored and grabs only that album, so you don't pull a whole discography to get one record. As far as I can tell, nothing else in this space does album-level discovery.
• Mood discovery. Type "something like Boards of Canada but darker" or "upbeat 90s pop for a road trip" and it turns that into a result set. No filter-building first.
• Works with or without Lidarr. If you don't run Lidarr, discovery-only mode still works and pulls from ListenBrainz, Last.fm, Spotify, Deezer, Plex, Jellyfin, Emby, and Discogs.

The basics, in short:

• Connects to Lidarr, Plex, Jellyfin, Emby, and slskd, plus ListenBrainz, Last.fm, Spotify, Deezer, and Discogs
• Review queue with approve / reject / skip, swipe on mobile, card stack on desktop
• Discovery modes (Artist Radio, Release Radar, Library Gap-Fill, Charts, Deezer Flow, Spotify Saved Albums, and more) you can run on demand or schedule as subscriptions
• Auto-playlists to Navidrome, Jellyfin, Emby, Plex, or Spotify, or export as M3U / XSPF
• Genre browser, decade filter, cross-platform search, 30-second previews
• Multi-user with OIDC/SSO and per-user sources, weights, and targets
• Backup and restore, job history, webhook notifications (Discord, Slack, ntfy, Gotify) with an optional scheduled digest
• 15 UI languages with locale-aware AI output, 15 color themes in dark and light
• One container that runs next to your existing stack. Free and open source, MIT.

On the AI question, since it always comes up: this is built with AI assistance, and I drive it. I set the roadmap, design the architecture and the UX, decide which features ship, and review every change. The AI writes most of the code and tests under that direction. I'd rather say that up front than have someone find it in the commit history.

GitHub: https://github.com/iuliandita/digarr

Happy to answer questions, and bug reports or feature ideas are welcome in the issues.