How To Run Rasa 3.5.10 on the Raspberry Pi 4!

I’ve noticed there are a few people on here asking how to install Rasa on the Raspberry Pi 4 and a lot of the answers are pretty outdated.

Here is a tutorial I made for running the latest version of Rasa, 3.5.10 on the Raspberry Pi 4. It works using Raspberry Pi OS (64-bit) and Ubuntu 23.04 (64-bit)

Special thanks to everyone on this old forum post and the work of @JulianGerhard which my tutorial is based off

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Installing Rasa 3.5.10 on Raspberry Pi 4 w/ Raspberry Pi OS 64-bit (Debian Bullseye)

Installing OS

To get started install the Raspberry Pi OS Imager

After installing the imager select CHOOSE OS > Raspberry Pi OS (other) > Raspberry Pi OS (64-bit)

  • NOTE: I have also tested that Rasa works with Ubuntu Desktop 23.04 (64-bit) on the Raspberry Pi as well so feel free to choose that if you prefer Ubuntu

Then select your storage device and write the image to it

Once you have finished writing the OS attach your storage device to your Raspberry Pi, power it on and go through the installation steps and restart the Pi when prompted

Adding Debian Bookworm to Debian Bullseye SourceList – Skip this step if you are using Ubuntu 23.04 –

To get the proper updated versions of some packages needed by Rasa’s package requirements we need to upgrade from Debian Bullseye to Bookworm

First open the source lists file from the terminal

sudo nano /etc/apt/sources.list

Then replace every instance of “bullseye” with “bookworm” in the first three lines. It should look as follows

deb bookworm main contrib non-free non-free-firmware
deb bookwork-security main contrib non-free non-free-firmware
deb bookworm-updates main contrib non-free non-free-firmware

Press Ctrl + s then Crtl + x to save and exit

Updating OS and Installing Required Packages

Once in the desktop open the terminal to update Debian and install the required packages. Select y to any prompts

sudo apt-get update
sudo apt-get upgrade -y 
sudo apt-get dist-upgrade -y

Now reboot the system and you should be in Debian Bookworm. – Ignore if using ubuntu –

  • NOTE: The default desktop environment may not look or work properly, if you’d like to change it follow this tutorial, I would recommend going with the gnome desktop option

Now lets install the required packages

sudo apt install -y build-essential git curl librdkafka-dev

Installing Mamba

Next we will install Mamba, this is a newer version of Conda that runs much faster and will help with installing all our Python packages

cd ~/Downloads

This will start the installation process. Go through the installer saying yes to all the options.

  • NOTE: this will cause Mamba to always activate when opening the terminal. To stop this you can issue the command “conda config --set auto_activate_base false”

Now close and reopen the terminal and you should see (base) added to the terminal line.

Update mamba by running these commands and selecting “y” to any prompts

mamba update mamba 
mamba update --all
  • NOTE: if you get an error after performing mamba update --all this should be okay, just rerun both commands and ensure everything is up to date

Setting Up A Virtual Environment

Now that Mamba is running and up to date we need to create a python environment for the project. This allows us to install whatever Python packages we want without clutering the main environment

We will be using python 3.10, selecting y to any prompts

mamba create -n RASA Python==3.10
mamba activate RASA
python -m pip uninstall pip
python -m ensurepip
python -m pip install -U pip

Installing Bazelisk

Next we install Bazelisk, this is a launcher for Bazel that will help with creating the Tensorflow Addons and Text Packages from source

cd ~/Downloads
chmod +x bazelisk-linux-arm64
sudo mv bazelisk-linux-amd64 /usr/local/bin/bazel

Now run the version command twice.

  • The first time will download the release to your machine.
  • The second time should confirm the bazel version
bazel --version

Installing Tensorflow

Now that we have all our tools setup and ready to go lets install Tensorflow version 2.11.0

pip install tensorflow==2.11.0

Installing Tensorflow Addons

Now we have to build Tensorflow Addons version 0.19 which is compatible with Tensorflow 2.11

cd ~/Downloads
git clone
cd addons
git checkout r0.19
python ./
bazel build --enable_runfiles build_pip_pkg
bazel-bin/build_pip_pkg artifacts
pip install artifacts/tensorflow_addons-0.19.0-*.whl

Installing Tensorflow Text

Now for the final requirement we build Tensorflow Text. This one will take a while so sit back, relax and make sure your Pi has a healthy power supply

cd ~/Downloads
git clone
cd text 
git checkout 2.11
source oss_scripts/
bazel build --enable_runfiles oss_scripts/pip_package/build_pip_package
./bazel-bin/oss_scripts/pip_package/build_pip_package artifacts
pip install artifacts/tensorflow_text-*.whl

Installing Rasa

And now for the moment of truth, we install Rasa

cd ~/Documents
mkdir Rasa
cd Rasa
pip install "rasa==3.5.10"
rasa init

Hopefully this helped, and happy training!

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