Install and uninstall WasmEdge

This chapter will discuss ways to install and uninstall the WasmEdge Runtime on various OSes and platforms. We will cover how to install plug-ins to WasmEdge.

備註

Docker Desktop 4.15+ already has WasmEdge bundled in its distribution binary. If you use Docker Desktop, you will not need to install WasmEdge separately. Check out how to run WasmEdge apps in Docker Desktop.

Install

You can install the WasmEdge Runtime on any generic Linux and MacOS platforms. If you use Windows 10 or Fedora / Red Hat Linux systems, you can install with their default package managers.

Generic Linux and MacOS

The easiest way to install WasmEdge is to run the following command. Your system should have git and curl as prerequisites.

curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash

Run the following command to make the installed binary available in the current session.

source $HOME/.wasmedge/env

Install for all users

WasmEdge is installed in the $HOME/.wasmedge directory by default. You can install it into a system directory, such as /usr/local to make it available to all users. To specify an install directory, run the install.sh script with the -p flag. You will need to run the following commands as the root user or sudo since they are written write into system directories.

curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash -s -- -p /usr/local

Install a specific version of WasmEdge

The WasmEdge installer script will install the latest official release by default. You could install a specific version of WasmEdge, including pre-releases or old releases by passing the -v argument to the installer script. Here is an example.

VERSION=0.14.1
curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash -s -- -v $VERSION

Suppose you are interested in the latest builds from the HEAD of the master branch, which is basically WasmEdge's nightly builds. In that case, you can download the release package directly from our Github Action's CI artifact. Here is an example.

Install via Nix

For nix/nixos users, we also provide a flake.nix in repository, so you can install WasmEdge via:

nix profile install github:WasmEdge/WasmEdge

Install WasmEdge with plug-ins

WasmEdge plug-ins are pre-built native modules that provide additional functionalities to the WasmEdge Runtime. To install plug-ins with the runtime, you can pass the --plugins parameter in the installer. For example, the command below installs the wasi_nn-ggml plug-in to enable LLM (Large Language Model) inference.

curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash -s -- --plugins wasi_nn-ggml

To install multiple plug-ins, you can pass a list of plug-ins with the --plugins option. For example, the following command installs the wasi_logging and the wasi_nn-ggml plug-ins. The wasi_logging plug-in allows the Rust log::Log API to compile into Wasm and run in WasmEdge.

curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash -s -- --plugins wasi_logging wasi_nn-ggml

The installer downloads the plug-in files from the WasmEdge release on GitHub, unzips them, and then copies them over to the ~/.wasmedge/plugin/ folder (for user install) and to the /usr/local/lib/wasmedge/ folder (for system install).

備註

The WASI-NN related plug-ins are all EXCLUSIVE. Users can only install one of the WASI-NN backends.

After WasmEdge 0.14.1, the WASI-Logging plug-in is bundled into the WasmEdge shared library and is not necessary to be installed.

Some of plug-ins need dependencies. Please follow the guide in the comment column to install the dependencies.

The following lists are the WasmEdge official released plug-ins. Users can install them easily by the parameters of --plugins option of installer.

Plug-in	Parameter	Supported Platforms	Versions	Comment
WASI-Logging	wasi_logging	All	Since 0.13.0	Bundled into WasmEdge library since 0.14.1.
WASI-Crypto	wasi_crypto	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.10.1
WASI-NN OpenVINO backend	wasi_nn-openvino	Linux (x86_64, Ubuntu only)	Since 0.10.1	Users should install the OpenVINO dependency.
WASI-NN PyTorch backend	wasi_nn-pytorch	Linux (x86_64)	Since 0.11.1	Users should install the PyTorch dependency.
WASI-NN TensorFlow-Lite backend	wasi_nn-tensorflowlite	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.11.2	Dependency installed automatically by installer.
WASI-NN GGML backend	wasi_nn-ggml	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.13.4	Notes for the dependency
WASI-NN Piper backend	wasi_nn-piper	Linux (x86_64, aarch64)	Since 0.14.1	Users should install the Piper dependency.
WASI-NN Whisper backend	wasi_nn-whisper	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.14.1
WASI-NN Burn.rs backend (Squeezenet)	wasi_nn_burnrs-squeezenet	Linux (x86_64, Ubuntu only)	Since 0.14.1
WASI-NN Burn.rs backend (Whisper)	wasi_nn_burnrs-whisper	Linux (x86_64, Ubuntu only)	Since 0.14.1
Ffmpeg	wasmedge_ffmpeg	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.14.0
Image	wasmedge_image	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.13.0
LLM	wasmedge_llmc	Linux (x86_64, aarch64)	Since 0.14.1
OpenCV mini	wasmedge_opencvmini	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.13.3
Process	wasmedge_process	Linux (x86_64, aarch64)	Since 0.10.0
Stable Diffusion	wasmedge_stablediffusion	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.14.1
TensorFlow	wasmedge_tensorflow	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.13.0	Dependency installed automatically by installer.
TensorFlow-Lite	wasmedge_tensorflowlite	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.13.0	Dependency installed automatically by installer.
Zlib	wasmedge_zlib	Linux (x86_64, aarch64), MacOS (x86_64, arm64)	Since 0.13.5
WASM-eBPF	wasm_bpf	Linux (x86_64)	Since 0.13.2
Rust TLS	wasmedge_rustls	Linux (x86_64)	Since 0.13.0	Until 0.13.5. DEPRECATED.

For further details of each plug-ins, please follow the plug-in page.

Windows

For Windows 10, you could use Windows Package Manager Client (aka winget.exe) to install WasmEdge with one single command in your terminal.

winget install wasmedge

To install plug-ins, you can download plug-in binary modules from the WasmEdge release page, unzip them, and then copy them to C:\Program Files\WasmEdge\lib.

Fedora and Red Hat Linux

WasmEdge is now an official package on Fedora 36, Fedora 37, Fedora 38, Fedora EPEL 8, and Fedora EPEL 9. Check out the stable version here. To install WasmEdge on Fedora, run the following command:

dnf install wasmedge

For more usages, please check out Fedora docs.

To install plug-ins, you can download plug-in binary modules from the WasmEdge release page, unzip them, and then copy them over to /usr/local/lib/wasmedge/.

What's installed

If you install into the $HOME/.wasmedge directory, you will have the following directories and files after installation:

• The $HOME/.wasmedge/bin directory contains the WasmEdge Runtime CLI executable files. You can copy and move them around on your file system.

  • The wasmedge tool is the standard WasmEdge runtime. You can use it from the CLI.

    • Execute a WASM file: wasmedge --dir .:. app.wasm

  • The wasmedgec tool is the ahead-of-time (AOT) compiler to compile a .wasm file into a native .so file (or .dylib on MacOS, .dll on Windows, or .wasm as the universal WASM format on all platforms). The wasmedge can then execute the output file.

    • Compile a WASM file into a AOT-compiled WASM: wasmedgec app.wasm app.so
    • Execute the WASM in AOT mode: wasmedge --dir .:. app.so
    備註

    The usage of wasmedgec is equal to wasmedge compile. We decide to deprecate wasmedgec in the future.

• The $HOME/.wasmedge/lib directory contains WasmEdge shared libraries and dependency libraries. They are useful for WasmEdge SDKs to launch WasmEdge programs and functions from host applications.

• The $HOME/.wasmedge/include directory contains the WasmEdge header files. They are useful for WasmEdge SDKs.

• The $HOME/.wasmedge/plugin directory contains the WasmEdge plug-ins. They are loadable extensions for WasmEdge SDKs and will automatically be loaded when running the WasmEdge CLI.

備註

You could also change it to /usr/local if you did a system-wide install. If you used winget to install WasmEdge, the files are located at C:\Program Files\WasmEdge.

Uninstall

To uninstall WasmEdge, you can run the following command:

bash <(curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/uninstall.sh)

If the wasmedge binary is not in PATH and it wasn't installed in the default $HOME/.wasmedge folder, then you must provide the installation path.

bash <(curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/uninstall.sh) -p /path/to/parent/folder

If you wish to uninstall uninteractively, you can pass in the --quick or -q flag.

bash <(curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/uninstall.sh) -q

備註

If a parent folder of the wasmedge binary contains .wasmedge, the folder will be considered for removal. For example, the script altogether removes the default $HOME/.wasmedge folder.

If you used dnf to install WasmEdge on Fedora and Red Hat Linux, run the following command to uninstall it:

dnf remove wasmedge

If you used winget to install WasmEdge on Windows, run the following command to uninstall it:

winget uninstall wasmedge

Appendix: Installing the Dependencies

GGML Dependencies

The installer from WasmEdge 0.13.5 will detect CUDA automatically. If CUDA is detected, the installer will always attempt to install a CUDA-enabled version of the WASI-NN GGML plug-in.

If CPU is the only available hardware on your machine, the installer will install OpenBLAS version of plugin instead.

apt update && apt install -y libopenblas-dev # You may need sudo if the user is not root.

TensorFlow-Lite Dependencies

If you install the WASI-NN TensorflowLite or WasmEdge-TensorFlowLite plug-in WITHOUT installer, you can download the shared libraries with the following commands:

VERSION=TF-2.12.0-CC
# For the WasmEdge versions before 0.13.0, please use the `TF-2.6.0-CC` version.
PLATFORM=manylinux2014_x86_64
# For the Linux aarch64 platforms, please use the `manylinux2014_aarch64`.
# For the MacOS x86_64 platforms, please use the `darwin_x86_64`.
# For the MacOS arm64 platforms, please use the `darwin_arm64`.
curl -s -L -O --remote-name-all https://github.com/second-state/WasmEdge-tensorflow-deps/releases/download/$VERSION/WasmEdge-tensorflow-deps-TFLite-$VERSION-$PLATFORM.tar.gz
tar -zxf WasmEdge-tensorflow-deps-TFLite-$VERSION-$PLATFORM.tar.gz
rm -f WasmEdge-tensorflow-deps-TFLite-$VERSION-$PLATFORM.tar.gz

The shared library will be extracted in the current directory ./libtensorflowlite_c.so (or .dylib for MacOS) and ./libtensorflowlite_flex.so (after the WasmEdge 0.13.0 version). You can move the library to the installation path:

# If you installed wasmedge locally as above
mv libtensorflowlite_c.so ~/.wasmedge/lib
mv libtensorflowlite_flex.so ~/.wasmedge/lib

# Or, if you installed wasmedge for all users in /usr/local/
mv libtensorflowlite_c.so /usr/local/lib
mv libtensorflowlite_flex.so /usr/local/lib

# Or on MacOS platforms
mv libtensorflowlite_c.dylib ~/.wasmedge/lib
mv libtensorflowlite_flex.dylib ~/.wasmedge/lib

TensorFlow Dependencies

If you install the WasmEdge-Tensorflow plug-in WITHOUT installer, you can download the shared libraries with the following commands:

VERSION=TF-2.12.0-CC
# For the WasmEdge versions before 0.13.0, please use the `TF-2.6.0-CC` version.
PLATFORM=manylinux2014_x86_64
# For the Linux aarch64 platforms, please use the `manylinux2014_aarch64`.
# For the MacOS x86_64 platforms, please use the `darwin_x86_64`.
# For the MacOS arm64 platforms, please use the `darwin_arm64`.
curl -s -L -O --remote-name-all https://github.com/second-state/WasmEdge-tensorflow-deps/releases/download/TF-2.12.0-CC/WasmEdge-tensorflow-deps-TF-TF-$VERSION-$PLATFORM.tar.gz
tar -zxf WasmEdge-tensorflow-deps-TF-TF-$VERSION-$PLATFORM.tar.gz
rm -f WasmEdge-tensorflow-deps-TF-TF-$VERSION-$PLATFORM.tar.gz

The shared library will be extracted in the current directory ./libtensorflow_cc.so.2.12.0 and ./libtensorflow_framework.so.2.12.0 on Linux platforms, or ./libtensorflow_cc.2.12.0.dylib and ./libtensorflow_framework.2.12.0.dylib on MacOS platforms. You can move the library to the installation path:

# If you installed wasmedge locally as above
mv libtensorflow_cc.so.2.12.0 ~/.wasmedge/lib
mv libtensorflow_framework.so.2.12.0 ~/.wasmedge/lib
ln -s libtensorflow_cc.so.2.12.0 ~/.wasmedge/lib/libtensorflow_cc.so.2
ln -s libtensorflow_cc.so.2 ~/.wasmedge/lib/libtensorflow_cc.so
ln -s libtensorflow_framework.so.2.12.0 ~/.wasmedge/lib/libtensorflow_framework.so.2
ln -s libtensorflow_framework.so.2 ~/.wasmedge/lib/libtensorflow_framework.so

# Or, if you installed wasmedge for all users in /usr/local/
mv libtensorflow_cc.so.2.12.0 /usr/local/lib
mv libtensorflow_framework.so.2.12.0 /usr/local/lib
ln -s libtensorflow_cc.so.2.12.0 /usr/local/lib/libtensorflow_cc.so.2
ln -s libtensorflow_cc.so.2 /usr/local/lib/libtensorflow_cc.so
ln -s libtensorflow_framework.so.2.12.0 /usr/local/lib/libtensorflow_framework.so.2
ln -s libtensorflow_framework.so.2 /usr/local/lib/libtensorflow_framework.so

# Or on MacOS platforms
mv libtensorflow_cc.2.12.0.dylib ~/.wasmedge/lib
mv libtensorflow_framework.2.12.0.dylib ~/.wasmedge/lib
ln -s libtensorflow_cc.2.12.0.dylib ~/.wasmedge/lib/libtensorflow_cc.2.dylib
ln -s libtensorflow_cc.2.dylib ~/.wasmedge/lib/libtensorflow_cc.dylib
ln -s libtensorflow_framework.2.12.0.dylib ~/.wasmedge/lib/libtensorflow_framework.2.dylib
ln -s libtensorflow_framework.2.dylib ~/.wasmedge/lib/libtensorflow_framework.dylib

OpenVINO Dependencies

The WASI-NN plug-in with OpenVINO backend depends on the OpenVINO C library to perform AI/ML computations. The following commands are for Ubuntu 20.04 and above to install OpenVINO(2023) dependencies.

wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
echo "deb https://apt.repos.intel.com/openvino/2023 ubuntu20 main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2023.list
sudo apt update
sudo apt-get -y install openvino
ldconfig

PyTorch Dependencies

The WASI-NN plug-in with PyTorch backend depends on the libtorch C++ library to perform AI/ML computations. You need to install the PyTorch 1.8.2 LTS dependencies for it to work properly.

export PYTORCH_VERSION="1.8.2"
# For the Ubuntu 20.04 or above, use the libtorch with cxx11 abi.
export PYTORCH_ABI="libtorch-cxx11-abi"
# For the manylinux2014, please use the without cxx11 abi version:
#   export PYTORCH_ABI="libtorch"
curl -s -L -O --remote-name-all https://download.pytorch.org/libtorch/lts/1.8/cpu/${PYTORCH_ABI}-shared-with-deps-${PYTORCH_VERSION}%2Bcpu.zip
unzip -q "${PYTORCH_ABI}-shared-with-deps-${PYTORCH_VERSION}%2Bcpu.zip"
rm -f "${PYTORCH_ABI}-shared-with-deps-${PYTORCH_VERSION}%2Bcpu.zip"
export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:$(pwd)/libtorch/lib

備註

For the Ubuntu 20.04 or above versions, the WasmEdge installer will install the Ubuntu version of WasmEdge and its plug-ins. For other systems, the WasmEdge installer will install the manylinux2014 version, and you should get the libtorch without cxx11-abi.

Piper Dependencies

The WASI-NN plug-in with Piper backend depends on the ONNX Runtime C++ API. For installation instructions, please refer to the installation table on the official website.

Example of installing ONNX Runtime 1.14.1 on Ubuntu:

curl -LO https://github.com/microsoft/onnxruntime/releases/download/v1.14.1/onnxruntime-linux-x64-1.14.1.tgz
tar zxf onnxruntime-linux-x64-1.14.1.tgz
mv onnxruntime-linux-x64-1.14.1/include/* /usr/local/include/
mv onnxruntime-linux-x64-1.14.1/lib/* /usr/local/lib/
rm -rf onnxruntime-linux-x64-1.14.1.tgz onnxruntime-linux-x64-1.14.1
ldconfig

Troubleshooting

Some users, especially in China, reported encountering the Connection refused error when trying to download the install.sh from the githubusercontent.com.

Please make sure your network connection can access github.com and githubusercontent.com via VPN.

# The error message
curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash
curl: (7) Failed to connect to raw.githubusercontent.com port 443: Connection refused