Using the Installation Script
The quickest and easiest way to install Kenzy is to use our installation script:
wget -q -O install.sh https://kenzy.ai/installer && sh install.sh
Running the script exactly as shown above will install Kenzy and all components. If you want to be more selective you can add options as follows:
-b= Install brain dependencies
-l= Install listener dependencies
-s= Install speaker dependencies
-w= Install watcher dependencies
-p= Install panel dependencies
-v [PATH]= Python virtual environment path (will create new if does not already exist)
Installer script has been tested on Ubuntu 22.04+, Debian Buster, and Raspberry Pi OS (Buster).
Kenzy is available through pip, but to use the built-in devices there are a few extra libraries you may require.
# Install PIP (Python package manager) if not already installed sudo apt-get -y install python3-pip # Install the required system packages sudo apt-get -y install \ python3-fann2 \ python3-pyaudio \ python3-pyqt5 \ python3-dev \ libespeak-ng1 \ festival \ festvox-us-slt-hts \ libportaudio2 \ portaudio19-dev \ libasound2-dev \ libatlas-base-dev \ cmake \ swig # Create your local environment and then activate it sudo apt-get -y install python3-venv mkdir -p ~/kenzy cd ~/kenzy python3 -m venv ./.venv --system-site-packages source ./.venv/bin/activate # Install the required build libraries python3 -m pip install scikit-build # Install core required runtime libraries python3 -m pip install urllib3 \ requests \ netifaces \ padatious # Install libraries for SpeakerDevice (Required only if using ```mimic3``` in place of festival) python3 -m pip install mycroft-mimic3-tts[all] # Install optional libraries for WatcherDevice python3 -m pip install opencv-contrib-python \ Pillow # Install optional libraries for KasaDevice python3 -m pip install asyncio \ python-kasa # Install optional libraries for ListenerDevice python3 -m pip install --upgrade numpy \ webrtcvad \ stt # If you have trouble with pyaudio then you may want try to upgrade it python3 -m pip install --upgrade pyaudio # For listener model management (optional) python3 -m pip install coqui-stt-module-manager # Install the kenzy module python3 -m pip install kenzy
NOTE: The installation of OpenCV is required when using the watcher device. This may take a while on the Raspberry Pi OS as it has to recompile some of the libraries. Patience is required here as the spinner icon appeared to get stuck several times in our tests... so just let it run until it completes. If it encounters a problem then it'll print out the error for additional troubleshooting.
If you prefer not to wait then you can install the opencv package that comes with most distributions however this version does not support facial recognition. To use the package instead then issue
apt-get install python3-opencv and remove the
opencv-contrib-python from the pip package list above. (This will spead up the installation time significantly on the Raspberry Pi at the cost of functionality.)
Troubleshooting: "Cannot find FANN libs"
If you encounter an error trying to install the kenzy module on the Raspberry Pi then you may need to add a symlink to the library FANN library. This is due to a bug/miss in the "find_fann" function within the Python FANN2 library as it doesn't look for the ARM architecture out-of-the-box. To fix it run the following:
Raspberry Pi (ARM)
sudo ln -s /usr/lib/arm-linux-gnueabihf/libdoublefann.so.2 /usr/local/lib/libdoublefann.so
Ubuntu 22.04 LTS (x86_64)
sudo ln -s /usr/lib/x86_64-linux-gnu/libdoublefann.so.2 /usr/local/lib/libdoublefann.so
Download the Speech Recognition Models
python3 -m kenzy --download-models
from kenzy.extras import download_models download_models("tflite")
You can execute Kenzy directly as a module. To do so try the following:
python3 -m kenzy
You can disable any of the built-in devices or containers with
--disable-builtin-[speaker, watcher, listener, panels, brain, container]. Use the
--help option for full listing of command line options including specifying a custom configuration file.
NOTE: The program will create/save a version of the configuration to
~/.kenzy/config.json along with any other data elements it requires for operation. The configuration file is fairly powerful and will allow you to add/remove devices and containers for custom configurations including 3rd party devices or custom skills.
Web Control Panel
If everything is working properly you should be able to point your device to the web control panel running on the Brain engine to test it out. The default URL is:
Help & Support
Help and additional details is available at https://kenzy.ai