As of June 2022, Rasa is not officially supported on Macs with ARM-based Apple Silicon processors. The solution described here should only be used as a workaround until official support arrives. It has been tested on a Macbook Pro with M1 Processor.
Docker, and native installation is supported. In both cases an Anaconda environment is created in which as many dependencies as possible are installed via pip based on the pyproject.toml of a specific Rasa release.
The remaining packages for which no arm64/aarch64 wheels are available on PyPI are fetched from Anaconda channels (conda-forge, noarch, and apple) or from Github repositories that offer precompiled wheels.
At the time of writing, the only dependency that could neither be satisfied from Pip nor Anaconda is tensorflow-text.
Therefore, projects that rely on Rasa features utilizing this package will not work.
The easiest way to get started is by using the Docker images on Dockerhub.
docker run -it --rm khalosa/rasa-aarch64:latestAlternatively, if you want to build the image yourself:
./build-docker.shIf you want to run Rasa natively on your Mac, you need to have these tools installed:
- Miniforge, arm64 (Apple Silicon) version
- Python 3 (
pip, andpythoncommands must point to a Python3 installation)
Now run this snippet in the root directory of the project:
# set rasa version
export RASA_VERSION="3.2.1"
# use the generator script to create a conda env file
python -m rasa_dc --platform native --rasa_version $RASA_VERSION
# use the env file to create a new conda environment
conda env create --name rasa-${RASA_VERSION} --file=output/rasa_${RASA_VERSION}_native_env.yml
# finally install Rasa without dependencies into the newly created conda environment
$HOME/miniforge3/envs/rasa-$RASA_VERSION/bin/pip install --no-deps rasa==$RASA_VERSIONNow you should be able to activate the created environment:
conda activate rasa-${RASA_VERSION}Verify that its working by executing rasa init.