Community Apps

This tool will publish Juicebox data from a UDP proxy to MQTT discoverable by HomeAssistant. Hopefully we won't need this if EnelX fixes their API! It is required that both your JuiceBox and the machine you are running juicepassproxy on have internal static IPs on your intranet.

Jump is a simple, stylish, fast and secure self-hosted startpage for your server. https://hub.docker.com/r/daledavies/jump/

Unraid compatible Jupyter Lab (Python kernel) container with GPU-optimized Tensorflow, PyTorch and OpenCV. The default password to access the Jupyter Lab is iti This is the GPU-bound container's version. Please note that the container images is large at over 18GB To use it requires the Nvidia driver installation on your Unraid server for support of Docker. This installation needs to support the version of CUDA installed to use with this container. If you have multiple GPUs in your system with some allocated to VMs, make sure to replace --gpus all with --runtime=nvidia and add the NVIDIA_DRIVER_CAPABILITIES and NVIDIA_VISIBLE_DEVICES environment variables to only give the container access to selected GPUs. A CPU equivalent container is also available and named Jupyter-TPO and is over 5GB The system is ran as the jupyter user (has sudo privileges) and /iti is where you can place your weights and other files to support your development. Please see https://github.com/Infotrend-Inc/CTPO for further details.

Unraid compatible Jupyter Notebook (Python kernel) container with GPU-optimized Tensorflow and OpenCV, and installations of Pandas, PyTorch -- based on datamachines/cudnn_tensorflow_opencv The default password to access Jupyter is dmc This is the GPU-bound container's version. Please note that the container images is large at over 16GB To use it requires the Nvidia driver installation on your Unraid server for support of Docker. This installation needs to support the version of CUDA installed to use with this container. If you have multiple GPUs in your system with some allocated to VMs, make sure to replace --gpus all with --runtime=nvidia and set the NVIDIA_DRIVER_CAPABILITIES and NVIDIA_VISIBLE_DEVICES variables to only give the container access to selected GPUs. A CPU equivalent container is also available and named Jupyter-TensorFlow_OpenCV and is over 4GB The system is ran as the jupyter user (has sudo privileges) and /dmc is where you can place your weights and other files to support your development. VERSION(s) (match datamachines/cudnn_tensorflow_opencv releases date) - 20220815 with support for CUDA 11.3.1, TensorFlow 2.9.1, OpenCV 4.6.0 and PyTorch 1.12.1 - 20220530 with support for CUDA 11.3.1, TensorFlow 2.9.1, OpenCV 4.5.5 and PyTorch 1.11 - 20220525 with support for CUDA 11.3.1, TensorFlow 2.9.1 and OpenCV 4.5.5 - 20220521 with support for CUDA 11.3.1, TensorFlow 2.9.0 and OpenCV 4.5.5 - 20220510 with support for CUDA 11.3.1, TensorFlow 2.8.0 and OpenCV 4.5.5 - 20220318 with support for CUDA 11.3.1, TensorFlow 2.8.0 and OpenCV 4.5.5 Changelog: - 20220815: latest is CUDA 11.3.1, TensorFlow 2.9.1, OpenCV 4.6.0 and PyTorch 1.12.1 (match version: 20220815) - 20220530: CUDA 11.3.1, TensorFlow 2.9.1, OpenCV 4.5.5 and PyTorch 1.11 (PyTorch is now built from source) (match version: 20220530) - 20220525: CUDA 11.3.1, TensorFlow 2.9.1 and OpenCV 4.5.5 (match version: 20220525) - 20220521: CUDA 11.3.1, TensorFlow 2.9.0 and OpenCV 4.5.5 (match version: 20220521) - 20220510: CUDA 11.3.1, TensorFlow 2.8.0 and OpenCV 4.5.5 (match version: 20220510) with updated base images including Nvidia's new package signing key - 20220422: Multiple GPUs note - 20220403: Updated unraid template - 20220402: Container updated to fix issue preventing change of default password (same components) - 20220331: Unraid initial release: latest is CUDA 11.3.1, TensorFlow 2.8.0 and OpenCV 4.5.5 (match version: 20220318)

Unraid compatible Jupyter Notebook (Python kernel) container with CPU-ready Tensorflow, OpenCV, Pandas, PyTorch -- based on datamachines/tensorflow_opencv The default password to access Jupyter is dmc This is the CPU-bound container's version. The GPU equivalent container is named Jupyter-CuDNN_TensorFlow_OpenCV Please note that the container images is large at over 4GB and its GPU counterpart runs over 16GB. The system is ran as the jupyter user (has sudo privileges) and /dmc is where you can place your weights and other files to support your development. VERSION(s) (match datamachines/tensorflow_opencv releases date) - 20220815 with support for TensorFlow 2.9.1, OpenCV 4.6.0 and PyTorch 1.12.1 - 20220530 with support for TensorFlow 2.9.1, OpenCV 4.5.5 and PyTorch 1.11 - 20220525 with support for TensorFlow 2.9.1 and OpenCV 4.5.5 - 20220521 with support for TensorFlow 2.9.0 and OpenCV 4.5.5 - 20220510 with support for TensorFlow 2.8.0 and OpenCV 4.5.5 - 20220318 with support for TensorFlow 2.8.0 and OpenCV 4.5.5 Changelog: - 20220815: latest is TensorFlow 2.9.1, OpenCV 4.6.0 and PyTorch 1.12.1 (match version: 20220815) - 20220530: TensorFlow 2.9.1, OpenCV 4.5.5 and PyTorch 1.11 (PyTorch is now built from source) (match version: 20220530) - 20220525: TensorFlow 2.9.1 and OpenCV 4.5.5 (match version: 20220525) - 20220521: TensorFlow 2.9.0 and OpenCV 4.5.5 (match version: 20220521) - 20220510: TensorFlow 2.8.0 and OpenCV 4.5.5 (match version: 20220510) with updated base images - 20220403: Updated unraid template - 20220402: Container updated to fix issue preventing change of default password (same components) - 20220331: Unraid initial release: latest is TensorFlow 2.8.0 and OpenCV 4.5.5 (match version: 20220318)

Unraid compatible Jupyter Lab (Python kernel) container with CPU-only Tensorflow, PyTorch and OpenCV. The default password to access the Jupyter Lab is iti This is the CPU-bound container's version. Please note that the container images is large at over 5GB A GPU equivalent container is also available and named Jupyter-CTPO and is over 18GB The system is ran as the jupyter user (has sudo privileges) and /iti is where you can place your weights and other files to support your development. Please see https://github.com/Infotrend-Inc/CTPO for further details.

JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. Links Repository: https://github.com/jupyterlab/jupyterlab Wiki: https://jupyterlab.readthedocs.io/en/stable Docker: https://hub.docker.com/repository/docker/bgameiro/arch-jupyterlab Configuration /opt/app/data Where JupyterLab should store the Notebooks Set Up The logs contain a token needed for first login Includes several python data science libraries and CERN's ROOT for HEP.

JupyterLab: A Next-Generation Notebook Interface JupyterLab is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. A modular design invites extensions to expand and enrich functionality. JupyterLabNN: A preconfigured Python environment set up for exploring neural networks including Large Language Models (LLMs).

Kanboard is project management software that focuses on the Kanban methodology.

Kapacitor is a native data processing engine for InfluxDB 1.x and is an integrated component in the InfluxDB 2.0 platform. Kapacitor can process both stream and batch data from InfluxDB, acting on this data in real-time via its programming language TICKscript.

Kapowarr allows you to build a digital library of comics. You can add volumes, map them to a folder and start managing! Download issues of the volume (or TPB's), rename them and move them. The whole process is automised and is all customisable in the settings.

Kasm(https://www.kasmweb.com/) Workspaces is a docker container streaming platform for delivering browser-based access to desktops, applications, and web services. Kasm uses devops-enabled Containerized Desktop Infrastructure (CDI) to create on-demand, disposable, docker containers that are accessible via web browser. Example use-cases include Remote Browser Isolation (RBI), Data Loss Prevention (DLP), Desktop as a Service (DaaS), Secure Remote Access Services (RAS), and Open Source Intelligence (OSINT) collections. The rendering of the graphical-based containers is powered by the open-source project KasmVNC(https://www.kasmweb.com/kasmvnc.html).

Kavita(https://github.com/Kareadita/Kavita) is a fast, feature rich, cross platform reading server. Built with a focus for being a full solution for all your reading needs. Setup your own server and share your reading collection with your friends and family!

Lightning fast with a slick design, Kavita is a rocket fueled self-hosted digital library which supports a vast array of file formats. Install to start reading comics, books and manga. You can also share your server with your friends! Important! Once you update to 0.8.0 or higher, you MUST perform a forced library scan on all libraries to migrate properly to the new foundation. Failure to do so may result in data loss.

KDE In Docker + VNC + noVNC Web UI Default Password: admin

Kdenlive(https://kdenlive.org/) is a powerful free and open source cross-platform video editing program made by the KDE community. Feature rich and production ready.

An instance of kdenlive accessible through vnc and noVnc (=Web Interface)

KeePassXC(https://keepassxc.org/) is a free and open-source password manager. It started as a community fork of KeePassX (itself a cross-platform port of KeePass).

The Keeper Automator service performs instant device approvals upon a successful login from the SSO identity provider. Once Automator is running, users can seamlessly access Keeper on a new (not previously approved) device after a successful authentication with your identity provider, without any further approval steps. More Information: https://docs.keeper.io/sso-connect-cloud/device-approvals/automator

This container will download and run Luna Multiplayer for Kerbal Space Program (KSP). Luna Multiplayer is a mod to enable Multiplayer for Kerbal Space Program, you can find more information here: https://github.com/LunaMultiplayer/LunaMultiplayer ATTENTION: Please also don't forget that you have to install the mod for your Client too: https://github.com/LunaMultiplayer/LunaMultiplayer/releases You can get detailed instructions on how to do that on the Wiki: https://github.com/LunaMultiplayer/LunaMultiplayer/wiki Update Notice: Simply restart the container if a newer version of the game is available and the container will download and install it.

Kerio Connect is Mail/Groupware like Microsoft Exchange, but running on Linux. More Informations under www.kerio.com/connect

Open Source Identity and Access Management.

Kibana gives shape to any kind of data — structured and unstructured — indexed in Elasticsearch. Please install and run Elasticsearch docker first. Set the tag to it to match the one you are using on Kibana (currently 7.12.0) Change ELASTIC_SEARCH_HOSTS to match the address of your Elasticsearch

KiCad(https://www.kicad.org/) - A Cross Platform and Open Source Electronics Design Automation Suite.

This Docker will download and install SteamCMD. It will also install Killing Floor and run it. To run this container you must provide a valid Steam username and password since the game needs a valid account to download (NOTICE: You must disable Steam Guard otherwise this container will not work, Steam recommens to make a new Steam account for dedicated servers). ATTENTION: First Startup can take very long since it downloads the gameserver files! Update Notice: Simply restart the container if a newer version of the game is available. You can also run multiple servers with only one SteamCMD directory!

This Docker will download and install SteamCMD. It will also install KillingFloor 2 and run it. ATTENTION: First Startup can take very long since it downloads the gameserver files! Update Notice: Simply restart the container if a newer version of the game is available. You can also run multiple servers with only one SteamCMD directory!

Kimai(https://kimai.org/) is a professional grade time-tracking application, free and open-source. It handles use-cases of freelancers as well as companies with dozens or hundreds of users. Kimai was build to track your project times and ships with many advanced features, including but not limited to: JSON API, invoicing, data exports, multi-timer and punch-in punch-out mode, tagging, multi-user - multi-timezones - multi-language (over 30 translations existing(https://hosted.weblate.org/projects/kimai/)!), authentication via SAML/LDAP/Database, two-factor authentication (2FA) with TOTP, customizable role and team permissions, responsive design, user/customer/project specific rates, advanced search and filtering, money and time budgets, advanced reporting, support for plugins(https://www.kimai.org/store/) and so much more.

Kimai is a professional grade time-tracking application, free and open-source. It handles use-cases of freelancers as well as companies with dozens or hundreds of users.

Kitana exposes your Plex plugin interfaces "to the outside world". It does that by authenticating against Plex.TV, then connecting to the Plex Media Server you tell it to, and essentially proxying the plugin UI. It has full PMS connection awareness and allows you to connect locally, remotely, or even via relay. To set the baseurl for this application, open advanced view, and add -p /kitana -P to the "Post Arguments"

KitchenOwl Backend Server. It's mandatory to also install the KitchenOwl-Web Container to access it from mobile and/or web. KitchenOwl is a self-hosted grocery list and recipe manager. The backend is made with Flask and the frontend with Flutter. Easily add items to your shopping list before you go shopping. You can also create recipes and add items based on what you want to cook.