docker-jellyfin/readme-vars.yml

---

# project information
project_name: jellyfin
project_url: "https://jellyfin.github.io/"
project_logo: "https://raw.githubusercontent.com/jellyfin/jellyfin-ux/master/branding/SVG/banner-logo-solid.svg?sanitize=true"
project_lsio_github_repo_url: "https://github.com/linuxserver/docker-{{ project_name }}"
project_blurb: "[{{ project_name|capitalize }}]({{ project_url }}) is a Free Software Media System that puts you in control of managing and streaming your media. It is an alternative to the proprietary Emby and Plex, to provide media from a dedicated server to end-user devices via multiple apps. Jellyfin is descended from Emby's 3.5.2 release and ported to the .NET Core framework to enable full cross-platform support. There are no strings attached, no premium licenses or features, and no hidden agendas: just a team who want to build something better and work together to achieve it."

# supported architectures
available_architectures:
  - { arch: "{{ arch_x86_64 }}", tag: "amd64-latest"}
  - { arch: "{{ arch_arm64 }}", tag: "arm64v8-latest"}
  - { arch: "{{ arch_armhf }}", tag: "arm32v7-latest"}

# development version
development_versions: true
development_versions_items:
  - { tag: "latest", desc: "Stable Jellyfin releases - Focal baseimage" }
  - { tag: "bionic", desc: "Stable Jellyfin releases - Bionic baseimage" }
  - { tag: "nightly", desc: "Nightly Jellyfin releases" }

# container parameters
common_param_env_vars_enabled: true #PGID, PUID, etc
param_container_name: "{{ project_name }}"
param_usage_include_vols: true
param_volumes:
  - { vol_path: "/config", vol_host_path: "/path/to/library", desc: "Jellyfin data storage location. *This can grow very large, 50gb+ is likely for a large collection.*" }
  - { vol_path: "/data/tvshows", vol_host_path: "/path/to/tvseries", desc: "Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc." }
  - { vol_path: "/data/movies", vol_host_path: "/path/to/movies", desc: "Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc." }
param_usage_include_ports: true
param_ports:
  - { external_port: "8096", internal_port: "8096", port_desc: "Http webUI." }
param_usage_include_env: true
param_env_vars:
  - { env_var: "TZ", env_value: "Europe/London", desc: "Specify a timezone to use EG Europe/London"}
# optional container parameters
opt_param_usage_include_env: true
opt_param_env_vars:
  - { env_var: "UMASK_SET", env_value: "<022>", desc: "for umask setting of Emby, default if left unset is 022."}
opt_param_usage_include_vols: true
opt_param_volumes:
  - { vol_path: "/opt/vc/lib", vol_host_path: "/opt/vc/lib", desc: "Path for Raspberry Pi OpenMAX libs *optional*." }
opt_param_device_map: true
opt_param_devices:
  - { device_path: "/dev/dri", device_host_path: "/dev/dri", desc: "Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi)." }
  - { device_path: "/dev/vcsm", device_host_path: "/dev/vcsm", desc: "Only needed if you want to use your Raspberry Pi MMAL video decoding (Enabled as OpenMax H264 decode in gui settings)." }
  - { device_path: "/dev/vchiq", device_host_path: "/dev/vchiq", desc: "Only needed if you want to use your Raspberry Pi OpenMax video encoding." }
  - { device_path: "/dev/video10", device_host_path: "/dev/video10", desc: "Only needed if you want to use your Raspberry Pi V4L2 video encoding." }
  - { device_path: "/dev/video11", device_host_path: "/dev/video11", desc: "Only needed if you want to use your Raspberry Pi V4L2 video encoding." }
  - { device_path: "/dev/video12", device_host_path: "/dev/video12", desc: "Only needed if you want to use your Raspberry Pi V4L2 video encoding." }
opt_param_usage_include_ports: true
opt_param_ports:
  - { external_port: "8920", internal_port: "8920", port_desc: "Optional - Https webUI (you need to set up your own certificate)." }
  - { external_port: "7359", internal_port: "7359/udp", port_desc: "Optional - Allows clients to discover Jellyfin on the local network." }
  - { external_port: "1900", internal_port: "1900/udp", port_desc: "Optional - Service discovery used by DNLA and clients." }
optional_parameters: |
  The [official documentation for ports](https://jellyfin.org/docs/general/networking/index.html) has additional ports that can provide auto discovery.

  Service Discovery (`1900/udp`) - Since client auto-discover would break if this option were configurable, you cannot change this in the settings at this time. DLNA also uses this port and is required to be in the local subnet.

  Client Discovery (`7359/udp`) - Allows clients to discover Jellyfin on the local network. A broadcast message to this port with "Who is Jellyfin Server?" will get a JSON response that includes the server address, ID, and name.

  ```
    -p 7359:7359/udp \
    -p 1900:1900/udp \
  ```

# application setup block
app_setup_block_enabled: true
app_setup_block: |
  Webui can be found at `http://<your-ip>:8096`

  More information can be found in their official documentation [here](https://jellyfin.org/docs/general/quick-start.html) .

  ## Hardware Acceleration
  
  ### Intel
  
  Hardware acceleration users for Intel Quicksync will need to mount their /dev/dri video device inside of the container by passing the following command when running or creating the container:

  `--device=/dev/dri:/dev/dri`

  We will automatically ensure the abc user inside of the container has the proper permissions to access this device.
  
  ### Nvidia
  
  Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:

  https://github.com/NVIDIA/nvidia-docker

  We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the jellyfin docker container.
  
  ### OpenMAX (Raspberry Pi)
  
  Hardware acceleration users for Raspberry Pi MMAL/OpenMAX will need to mount their `/dev/vcsm` and `/dev/vchiq` video devices inside of the container and their system OpenMax libs by passing the following options when running or creating the container:

  ```
  --device=/dev/vcsm:/dev/vcsm
  --device=/dev/vchiq:/dev/vchiq
  -v /opt/vc/lib:/opt/vc/lib
  ```

  ### V4L2 (Raspberry Pi)
  
  Hardware acceleration users for Raspberry Pi V4L2 will need to mount their `/dev/video1X` devices inside of the container by passing the following options when running or creating the container:

  ```
  --device=/dev/video10:/dev/video10
  --device=/dev/video11:/dev/video11
  --device=/dev/video12:/dev/video12
  ```


# changelog
changelogs:
  - { date: "23.11.20:", desc: "Rebase to Focal, branch off Bionic." }
  - { date: "22.07.20:", desc: "Ingest releases from Jellyfin repo." }
  - { date: "28.04.20:", desc: "Replace MMAL/OMX dependency device `/dev/vc-mem` with `/dev/vcsm` as the former was not sufficient for raspbian." }
  - { date: "11.04.20:", desc: "Enable hw decode (mmal) on Raspberry Pi, update readme instructions, add donation info, create missing default transcodes folder." }
  - { date: "11.03.20:", desc: "Add Pi V4L2 support, remove optional transcode mapping (location is selected in the gui, defaults to path under `/config`)." }
  - { date: "30.01.20:", desc: "Add nightly tag." }
  - { date: "09.01.20:", desc: "Add Pi OpenMax support." }
  - { date: "02.10.19:", desc: "Improve permission fixing for render & dvb devices." }
  - { date: "31.07.19:", desc: "Add AMD drivers for vaapi support on x86." }
  - { date: "13.06.19:", desc: "Add Intel drivers for vaapi support on x86." }
  - { date: "07.06.19:", desc: "Initial release." }