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Depending on your workflow, you may prefer to install go-livepeer using a binary release, a Docker image, or from source.

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Install using a Binary Release

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Dependencies

# For ubuntu
apt install curl coreutils gnupg2

# For macOS
brew install curl coreutils gnupg

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Darwin (macOS)

# <RELEASE_VERSION> is the release version, e.g. v0.5.35
# <ARCH> is the chip architecture (use arm64 for M1 and amd64 for Intel)

wget https://github.com/livepeer/go-livepeer/releases/download/<RELEASE_VERSION>/livepeer-darwin-<ARCH>.tar.gz

# Next, extract it
tar -zxvf livepeer-darwin-<ARCH>.tar.gz

# Finally, move it to the appropriate directory
mv livepeer-darwin-<ARCH>/* /usr/local/bin/

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Linux

# <RELEASE_VERSION> is the release version, e.g. v0.5.35
# <ARCH> is the chip architecture (use arm64 or amd64)

# Fetch the latest release
wget https://github.com/livepeer/go-livepeer/releases/download/<RELEASE_VERSION>/livepeer-linux-<ARCH>.tar.gz

# Next, extract it
tar -zxvf livepeer-linux-amd64.tar.gz

# Finally, move it to the appropriate directory
mv livepeer-linux-amd64/* /usr/local/bin/

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Linux GPU

There is a separate binary which supports transcoding on the NVIDIA GPU. The requirement for this binary is to have version 12 of the CUDA Toolkit installed on your machine. 
# <RELEASE_VERSION> is the release version, e.g. v0.5.35
# <ARCH> is the chip architecture (use arm64 or amd64)

# Fetch the latest release
wget https://github.com/livepeer/go-livepeer/releases/download/<RELEASE_VERSION>/livepeer-linux-gpu-<ARCH>.tar.gz

# Next, extract it
tar -zxvf livepeer-linux-gpu-<ARCH>.tar.gz

# Finally, move it to the appropriate directory
mv livepeer-linux-gpu-<ARCH>/* /usr/local/bin/

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Windows

# <RELEASE_VERSION> is the release version, e.g. v0.5.35

# Fetch the latest release .zip
wget https://github.com/livepeer/go-livepeer/releases/download/<RELEASE_VERSION>/livepeer-windows-amd64.zip

# Next, extract it
unzip livepeer-windows-amd64.zip

# Finally, move it to the appropriate directory, e.g. C:\Users\UserName\livepeer-folder
move livepeer-windows-amd64 e.g. C:\Users\UserName\livepeer-folder
At this time Livepeer does not provide automatic updates. You can perform a manual update or use a script. A community-created Bash script to update Livepeer is available on the livepeer Forum.

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Third-party packages

Packages for different Linux distributions are maintained by Livepeer community members. Before using these packages, please verify that they have been updated to use the latest builds of go-livepeer. This list will be updated as a best-effort, but we cannot guarantee if individual packages are up to date or verify their integrity. In the future, Livepeer core contributors may publish official packages for the distributions below.
PlatformInstallationSource
Arch Linuxparu go-livepeer-binhttps://aur.archlinux.org/packages/go-livepeer-bin/

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Install using a Docker image

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Prerequisites

If you do not have Docker installed, you will need to install it using the guide here before running the commands below.

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Installation

With every release, Docker images are pushed to DockerHub. 
# <RELEASE_VERSION> is the release version i.e. 0.5.14
docker pull livepeer/go-livepeer:<RELEASE_VERSION>

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Running livepeer-cli with Docker

Once you’ve pulled the image, retrieve the image id and start the container. Any flags you provide will be passed to the binary, so you can pass your configuration flags here. 
docker run <image id> <livepeer configuration flags>

# GPU support (Transcoder-only)
docker run --gpus all <image id> <livepeer configuration flags>
Once you’ve started the container, retrieve the name and start the CLI 
docker exec -it <container_name> livepeer_cli

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Installing pre-releases with Docker

To pull the latest pre-release version: 
docker pull livepeer/go-livepeer:master

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Build from source

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System dependencies

Building livepeer requires some system dependencies.

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Linux (Ubuntu: 16.04 or 18.04)

apt-get update && apt-get -y install build-essential pkg-config autoconf git curl yasm

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Linux (Ubuntu: 20.04 or newer)

apt-get -y install protobuf-compiler-grpc golang-goprotobuf-dev yasm pkg-config

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Linux GPU support

To enable transcoding using Nvidia GPUs on Linux systems
  • CUDA Toolkit must be installed on the system and available on the LIBRARY_PATH
  • clang must be installed as well. The script that will install ffmpeg dependencies uses which clang command to determine whether clang is installed or not. Please check this on your system. If the path is empty, please install clang. For example on the Ubuntu machine one can do
apt-get -y install clang clang-tools
export LIBRARY_PATH="/usr/local/cuda/lib64:${LIBRARY_PATH}"

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Darwin (macOS)

brew update && brew install pkg-config autoconf

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Go

Building livepeer requires Go. Follow the official Go installation instructions.

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Build and install

  1. Clone the repository:
git clone https://github.com/livepeer/go-livepeer.git
cd go-livepeer
  1. Install ffmpeg dependencies:
./install_ffmpeg.sh
  1. Set build environment variables.
Set the PKG_CONFIG_PATH variable so that pkg-config can find the ffmpeg dependency files installed in step 2: 
# install_ffmpeg.sh stores ffmpeg dependency files in this directory by default
export PKG_CONFIG_PATH=~/compiled/lib/pkgconfig
Set the BUILD_TAGS variable to enable mainnet support: 
export BUILD_TAGS=mainnet
# To build with support for only development networks and the Rinkeby test network
# export BUILD_TAGS=rinkeby
# To build with support for only development networks
# export BUILD_TAGS=dev
  1. Build and install livepeer:
make
cp livepeer* /usr/local/bin

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Troubleshooting

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Error while loading shared libraries

You may encounter the following issue when running the livepeer binary. 
error while loading shared libraries: libnppig.so.11: cannot open shared object file: No such file or directory.
This means that you have installed the Livepeer GPU binary but it is unable to access your CUDA Toolkit libraries. If you do not intend to use GPU transcoding, please download livepeer instead of livepeer-gpu. However, if you wish to use GPU transcoding, please ensure that the CUDA Toolkit is installed and add its path to the shared libraries path. 
export LD_LIBRARY_PATH=${HOME}/compiled/lib:/usr/local/cuda/lib64:${LD_LIBRARY_PATH}