Project Icon

jellyfin

开源跨平台媒体服务器和流媒体解决方案

Jellyfin是一个开源的跨平台媒体服务器系统,支持自主管理和流式传输个人媒体内容。它提供多种客户端应用,可在不同设备上访问媒体库,无需付费许可或隐藏功能。Jellyfin由开发者社区维护,致力于改进媒体管理体验。用户可以方便地搭建私人媒体中心,随时随地欣赏自己的音视频收藏。

Jellyfin

The Free Software Media System


Logo Banner

GPL 2.0 License Current Release Translation Status Docker Pull Count
Donate Submit Feature Requests Chat on Matrix Release RSS Feed Master Commits RSS Feed


Jellyfin 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. We welcome anyone who is interested in joining us in our quest!

For further details, please see our documentation page. To receive the latest updates, get help with Jellyfin, and join the community, please visit one of our communication channels. For more information about the project, please see our about page.

Want to get started?
Check out our downloads page or our installation guide, then see our quick start guide. You can also build from source.

Something not working right?
Open an Issue on GitHub.

Want to contribute?
Check out our contributing choose-your-own-adventure to see where you can help, then see our contributing guide and our community standards.

New idea or improvement?
Check out our feature request hub.

Don't see Jellyfin in your language?
Check out our Weblate instance to help translate Jellyfin and its subprojects.

Detailed Translation Status

Jellyfin Server

This repository contains the code for Jellyfin's backend server. Note that this is only one of many projects under the Jellyfin GitHub organization on GitHub. If you want to contribute, you can start by checking out our documentation to see what to work on.

Server Development

These instructions will help you get set up with a local development environment in order to contribute to this repository. Before you start, please be sure to completely read our guidelines on development contributions. Note that this project is supported on all major operating systems except FreeBSD, which is still incompatible.

Prerequisites

Before the project can be built, you must first install the .NET 8.0 SDK on your system.

Instructions to run this project from the command line are included here, but you will also need to install an IDE if you want to debug the server while it is running. Any IDE that supports .NET 6 development will work, but two options are recent versions of Visual Studio (at least 2022) and Visual Studio Code.

ffmpeg will also need to be installed.

Cloning the Repository

After dependencies have been installed you will need to clone a local copy of this repository. If you just want to run the server from source you can clone this repository directly, but if you are intending to contribute code changes to the project, you should set up your own fork of the repository. The following example shows how you can clone the repository directly over HTTPS.

git clone https://github.com/jellyfin/jellyfin.git

Installing the Web Client

The server is configured to host the static files required for the web client in addition to serving the backend by default. Before you can run the server, you will need to get a copy of the web client since they are not included in this repository directly.

Note that it is also possible to host the web client separately from the web server with some additional configuration, in which case you can skip this step.

There are three options to get the files for the web client.

  1. Download one of the finished builds from the Azure DevOps pipeline. You can download the build for a specific release by looking at the branches tab of the pipelines page.
  2. Build them from source following the instructions on the jellyfin-web repository
  3. Get the pre-built files from an existing installation of the server. For example, with a Windows server installation the client files are located at C:\Program Files\Jellyfin\Server\jellyfin-web

Running The Server

The following instructions will help you get the project up and running via the command line, or your preferred IDE.

Running With Visual Studio

To run the project with Visual Studio you can open the Solution (.sln) file and then press F5 to run the server.

Running With Visual Studio Code

To run the project with Visual Studio Code you will first need to open the repository directory with Visual Studio Code using the Open Folder... option.

Second, you need to install the recommended extensions for the workspace. Note that extension recommendations are classified as either "Workspace Recommendations" or "Other Recommendations", but only the "Workspace Recommendations" are required.

After the required extensions are installed, you can run the server by pressing F5.

Running From the Command Line

To run the server from the command line you can use the dotnet run command. The example below shows how to do this if you have cloned the repository into a directory named jellyfin (the default directory name) and should work on all operating systems.

cd jellyfin                          # Move into the repository directory
dotnet run --project Jellyfin.Server --webdir /absolute/path/to/jellyfin-web/dist # Run the server startup project

A second option is to build the project and then run the resulting executable file directly. When running the executable directly you can easily add command line options. Add the --help flag to list details on all the supported command line options.

  1. Build the project
dotnet build                       # Build the project
cd Jellyfin.Server/bin/Debug/net8.0 # Change into the build output directory
  1. Execute the build output. On Linux, Mac, etc. use ./jellyfin and on Windows use jellyfin.exe.

Accessing the Hosted Web Client

If the Server is configured to host the Web Client, and the Server is running, the Web Client can be accessed at http://localhost:8096 by default.

API documentation can be viewed at http://localhost:8096/api-docs/swagger/index.html

Running from GitHub Codespaces

As Jellyfin will run on a container on a GitHub hosted server, JF needs to handle some things differently.

NOTE: Depending on the selected configuration (if you just click 'create codespace' it will create a default configuration one) it might take 20-30 seconds to load all extensions and prepare the environment while VS Code is already open. Just give it some time and wait until you see Downloading .NET version(s) 7.0.15~x64 ...... Done! in the output tab.

NOTE: If you want to access the JF instance from outside, like with a WebClient on another PC, remember to set the "ports" in the lower VS Code window to public.

NOTE: When first opening the server instance with any WebUI, you will be sent to the login instead of the setup page. Refresh the login page once and you should be redirected to the Setup.

There are two configurations for you to choose from.

Default - Development Jellyfin Server

This creates a container that has everything to run and debug the Jellyfin Media server but does not setup anything else. Each time you create a new container you have to run through the whole setup again. There is also no ffmpeg, webclient or media preloaded. Use the .NET Launch (nowebclient) launch config to start the server.

Keep in mind that as this has no web client you have to connect to it via an external client. This can be just another codespace container running the WebUI. vuejs does not work from the get-go as it does not support the setup steps.

Development Jellyfin Server ffmpeg

this extends the default server with a default installation of ffmpeg6 though the means described here: https://jellyfin.org/docs/general/installation/linux#repository-manual If you want to install a specific ffmpeg version, follow the comments embedded in the .devcontainer/Dev - Server Ffmpeg/install.ffmpeg.sh file.

Use the ghcs .NET Launch (nowebclient, ffmpeg) launch config to run with the jellyfin-ffmpeg enabled.

Running The Tests

This repository also includes unit tests that are used to validate functionality as part of a CI pipeline on Azure. There are several ways to run these tests.

  1. Run tests from the command line using dotnet test
  2. Run tests in Visual Studio using the Test Explorer
  3. Run individual tests in Visual Studio Code using the associated CodeLens annotation

Advanced Configuration

The following sections describe some more advanced scenarios for running the server from source that build upon the standard instructions above.

Hosting The Web Client Separately

It is not necessary to host the frontend web client as part of the backend server. Hosting these two components separately may be useful for frontend developers who would prefer to host the client in a separate webpack development server for a tighter development loop. See the jellyfin-web repo for instructions on how to do this.

To instruct the server not to host the web content, there is a nowebclient configuration flag that must be set. This can be specified using the command line switch --nowebclient or the environment variable JELLYFIN_NOWEBCONTENT=true.

Since this is a common scenario, there is also a separate launch profile defined for Visual Studio called Jellyfin.Server (nowebcontent) that can be selected from the 'Start Debugging' dropdown in the main toolbar.

NOTE: The setup wizard cannot be run if the web client is hosted separately.


This project is supported by:

DigitalOcean  

项目侧边栏1项目侧边栏2
推荐项目
Project Cover

豆包MarsCode

豆包 MarsCode 是一款革命性的编程助手,通过AI技术提供代码补全、单测生成、代码解释和智能问答等功能,支持100+编程语言,与主流编辑器无缝集成,显著提升开发效率和代码质量。

Project Cover

AI写歌

Suno AI是一个革命性的AI音乐创作平台,能在短短30秒内帮助用户创作出一首完整的歌曲。无论是寻找创作灵感还是需要快速制作音乐,Suno AI都是音乐爱好者和专业人士的理想选择。

Project Cover

有言AI

有言平台提供一站式AIGC视频创作解决方案,通过智能技术简化视频制作流程。无论是企业宣传还是个人分享,有言都能帮助用户快速、轻松地制作出专业级别的视频内容。

Project Cover

Kimi

Kimi AI助手提供多语言对话支持,能够阅读和理解用户上传的文件内容,解析网页信息,并结合搜索结果为用户提供详尽的答案。无论是日常咨询还是专业问题,Kimi都能以友好、专业的方式提供帮助。

Project Cover

阿里绘蛙

绘蛙是阿里巴巴集团推出的革命性AI电商营销平台。利用尖端人工智能技术,为商家提供一键生成商品图和营销文案的服务,显著提升内容创作效率和营销效果。适用于淘宝、天猫等电商平台,让商品第一时间被种草。

Project Cover

吐司

探索Tensor.Art平台的独特AI模型,免费访问各种图像生成与AI训练工具,从Stable Diffusion等基础模型开始,轻松实现创新图像生成。体验前沿的AI技术,推动个人和企业的创新发展。

Project Cover

SubCat字幕猫

SubCat字幕猫APP是一款创新的视频播放器,它将改变您观看视频的方式!SubCat结合了先进的人工智能技术,为您提供即时视频字幕翻译,无论是本地视频还是网络流媒体,让您轻松享受各种语言的内容。

Project Cover

美间AI

美间AI创意设计平台,利用前沿AI技术,为设计师和营销人员提供一站式设计解决方案。从智能海报到3D效果图,再到文案生成,美间让创意设计更简单、更高效。

Project Cover

稿定AI

稿定设计 是一个多功能的在线设计和创意平台,提供广泛的设计工具和资源,以满足不同用户的需求。从专业的图形设计师到普通用户,无论是进行图片处理、智能抠图、H5页面制作还是视频剪辑,稿定设计都能提供简单、高效的解决方案。该平台以其用户友好的界面和强大的功能集合,帮助用户轻松实现创意设计。

投诉举报邮箱: service@vectorlightyear.com
@2024 懂AI·鲁ICP备2024100362号-6·鲁公网安备37021002001498号