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Getting RASA to Work on the Raspberry Pi 4 (Buster)

See original GitHub issue

Rasa version: 1.3.8

Rasa X version: N/A

Python version: 3.5

Operating system (windows, osx, …): Raspbian Buster

Issue:

I am in the process of trying to install Rasa on my Raspberry Pi 4 (4GB RAM edition) and I continue running into an error with installing or-tools stating:

  ERROR: Could not find a version that satisfies the requirement ortools (from mesh-tensorflow->tensor2tensor~=1.14.0->rasa) (from versions: none)
ERROR: No matching distribution found for ortools (from mesh-tensorflow->tensor2tensor~=1.14.0->rasa)

Any suggestions on any potential work-arounds?

Here is what I tried so far:

I tried to build or-tools on an x86_64 based computer running linux. Once I had it successfully built, I transfered it to the Pi and even though I could import ortools, I could not perform any operations using it.
Attempted to build or-tools on the Pi via these instructions but, given that the instructions are two years old and or-tools has changed dramatically, the process fails with the RPi’s CPU spiking to 300% before shutting off. I also tried this process on my linux computer and it almost overloaded my 8GB of RAM - so it is a fairly intensive task!

Another thought was to build a wheel for or-tools that could be compatible with arm7l architecture, but I do not know how feasible this is - it could be bundled with future releases of rasa.

Replication of Error Procedure

Here are the steps I took to get to this point; follow it completely to replicate my error:

Freshly install a new version of Raspbian Lite (Buster) on an SD Card

Run the following to update the Raspberry Pi:

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

Install Berryconda package manager:

wget https://github.com/jjhelmus/berryconda/releases/download/v2.0.0/Berryconda3-2.0.0-Linux-armv7l.sh &&
chmod +x Berryconda3-2.0.0-Linux-armv7l.sh &&
./Berryconda3-2.0.0-Linux-armv7l.sh && sudo reboot

Add RPI channel into conda:

conda config --add channels rpi
Install Python3.5 into conda:

conda install python=3.5 -y
Set-Up conda environment (we set-up with 3.5 so as to not encounter an error with open-cv):

A. Create conda environment: conda create --name alpha python=3.5 pip -y

B. Update all packages in conda environment:
```
conda update --all -y &&
source activate alpha &&
pip install --upgrade pip setuptools wheel
```
Install rasa:

A. Install required system packages:

sudo apt-get install libatlas-base-dev python3-dev python3-pip libhdf5-dev -y

B. Reboot the computer

sudo reboot

C. Install rasa

source activate alpha && pip install rasa

Error (including full traceback):

Looking in indexes: https://pypi.org/simple, https://www.piwheels.org/simple
Collecting rasa
  Using cached https://files.pythonhosted.org/packages/94/04/183500ce584fc4dce09ccdb80e192f90ae5ba61553ace9e17b3f77c94a04/rasa-1.3.9-py3-none-any.whl
Collecting python-socketio>=4.3.1 (from rasa)
  Downloading https://files.pythonhosted.org/packages/35/b0/22c3f785f23fec5c7a815f47c55d7e7946a67ae2129ff604148e939d3bdb/python_socketio-4.3.1-py2.py3-none-any.whl (49kB)
Collecting aiohttp~=3.5 (from rasa)
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Collecting packaging~=19.0 (from rasa)
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Collecting scikit-learn~=0.20.0 (from rasa)
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Collecting networkx~=2.3 (from rasa)
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Collecting tensorflow-probability~=0.7.0 (from rasa)
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Collecting tensorflow~=1.14.0 (from rasa)
  Downloading https://www.piwheels.org/simple/tensorflow/tensorflow-1.14.0-cp35-none-linux_armv7l.whl (100.7MB)
Collecting sanic-jwt~=1.3 (from rasa)
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Collecting SQLAlchemy~=1.3.0 (from rasa)
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Collecting python-telegram-bot~=11.0 (from rasa)
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Collecting pykwalify~=1.7.0 (from rasa)
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Collecting twilio~=6.0 (from rasa)
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Collecting python-dateutil~=2.8 (from rasa)
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Collecting requests>=2.20 (from rasa)
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Collecting rasa-sdk~=1.3.0 (from rasa)
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Collecting pika~=1.0.0 (from rasa)
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Collecting python-engineio>=3.9.3 (from rasa)
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Collecting redis~=3.3.5 (from rasa)
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Collecting sanic~=19.3.1 (from rasa)
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Collecting matplotlib~=3.0 (from rasa)
  Downloading https://www.piwheels.org/simple/matplotlib/matplotlib-3.0.3-cp35-cp35m-linux_armv7l.whl (10.9MB)
Collecting gast==0.2.2 (from rasa)
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Collecting sklearn-crfsuite~=0.3.6 (from rasa)
  Downloading https://files.pythonhosted.org/packages/25/74/5b7befa513482e6dee1f3dd68171a6c9dfc14c0eaa00f885ffeba54fe9b0/sklearn_crfsuite-0.3.6-py2.py3-none-any.whl
Collecting gevent~=1.4 (from rasa)
  Downloading https://www.piwheels.org/simple/gevent/gevent-1.4.0-cp35-cp35m-linux_armv7l.whl (5.6MB)
Collecting kafka-python~=1.4 (from rasa)
  Downloading https://files.pythonhosted.org/packages/49/c9/9863483a1353700ba87821b4f39085eb18fd1bcbb1e954c697177d67f03f/kafka_python-1.4.7-py2.py3-none-any.whl (266kB)
Collecting PyJWT~=1.7 (from rasa)
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Collecting webexteamssdk~=1.1 (from rasa)
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Collecting six>=1.9.0 (from python-socketio>=4.3.1->rasa)
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Collecting chardet<4.0,>=2.0 (from aiohttp~=3.5->rasa)
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Collecting async-timeout<4.0,>=3.0 (from aiohttp~=3.5->rasa)
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Collecting idna-ssl>=1.0; python_version < "3.7" (from aiohttp~=3.5->rasa)
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Collecting pyparsing>=2.0.2 (from packaging~=19.0->rasa)
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Collecting decorator>=4.3.0 (from networkx~=2.3->rasa)
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Collecting cloudpickle>=0.6.1 (from tensorflow-probability~=0.7.0->rasa)
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ERROR: No matching distribution found for ortools (from mesh-tensorflow->tensor2tensor~=1.14.0->rasa)

Command which led to error:

pip install rasa

If you have any questions, feel free to reach out - I hope we can get this working!

Issue Analytics

State:
Created 4 years ago
Comments:48 (25 by maintainers)

Top GitHub Comments

7reactions

JulianGerhard21commented, Oct 21, 2019

Hi guys, (@wochinge @TheCedarPrince @akelad)

I was now able to set everything up properly. I had the following setup, but tried to make everything as flexible as possible so at least Raspian 9 should be supported aswell:

Device: Raspberry Pi 4 OS: Raspbian 10 Python: 3.6.8 Frameworks to install: Tensorflow, SpaCy, Rasa

The following steps are necessary or recommended:

Update your OS with sudo apt-get update && apt-get upgrade
At the time writing this, Raspbian 10 ships with python 3.7.3 as default - which currently is not officially supported by Tensorflow. To workaround this, we are going to install python 3.6.8 in several steps. Note that bz2 is needed by Rasa and not per default compiled with python.

2.1 Install the bzip2 development library with sudo apt-get install libbz2-dev libssl-dev 2.2 Download the python 3.6.8 tarfile 2.3 Enter the following commands in your terminal:

tar -xvf Python-3.6.8.tar.xz
cd Python-3.6.8.tar.xz
sudo ./configure
sudo make -j4
sudo make install

To confirm that your installation works, you can do:

python3.6 -V
python3.6 -m pip -V

Update pip and setuptools with python3.6 -m pip install --upgrade pip --user and python3.6 -m pip install --upgrade setuptools --user (necessary to be able to install the latest wheels/libs)
Install Tensorflow with python3.6 -m pip install tensorflow==1.14.0 --user

There should not occur problems until this point. Now things are getting a bit more complicated since we are entering areas where compatibility is not given and we need to build/modify things. First of all we need to clone certain repositories (clone in separate directories is recommended):

a. git clone https://github.com/explosion/spaCy b. git clone https://github.com/tensorflow/tensor2tensor c. wget https://github.com/RasaHQ/rasa/archive/1.4.0.zip

Follow this OpenCV tutorial from step 2 on until OpenCV is successfully installed. You should be able to do “import cv2” in python3.6 then. If there is an error, don’t worry - OpenCV is not mandatory.
Execute the following command in terminal: export BLIS_ARCH=generic (blis is used for computational purposes and mandatory for spacy)
Move into the spaCy folder and use python3.6 -m pip install -r requirements.txt --user
Move into the spaCy folder and execute python setup.py build_ext --inplace
Move into the spaCy folder and execute python3.6 -m pip install . --user
Execute the following command in terminal: python3.6 -m pip install dopamine-rl --user --no-deps (there is a cyclic behaviour in the dependencies of dopamine which is a dependency of tensor2tensor so we are just simplifying things here).
Move into the tensor2tensor folder and remove the following dependency from setup.py: opencv-python (we have installed this previously but there is no symlink created so python won’t find it easily)
Move into the tensor2tensor folder and use python3.6 -m pip install . --user --force-reinstall

At this time, we have successfully installed Tensorflow, SpaCy and several dependencies that are getting important now.

Execute the following commands in terminal: sudo apt install python3-dev && apt install libpq-dev/buster (per default, there is to postgres system installed but rasa has the requirement psycopg2)
Execute the following command: python3.6 -m pip install psycopg2 --user
Move into the Rasa-1.4.0 folder and remove the following dependency from requirements.txt and setup.py: tensor2tensor (we have installed this previously)
Move into the Rasa-1.4.0 folder and execute: python3.6 -m pip install -r requirements.txt --user --force-reinstall
Move into the Rasa-1.4.0 folder and execute: python3.6 -m pip install . --user --force-reinstall

Now you should be able to run: python3.6 -m rasa init and e.g. use pretrained_embeddings_spacy as a pipeline (assuming you downloaded at least one model from spacy).

General notes:

The main problems are missing wheels for Raspbian/Debian 10, compatibility issues with various python versions and the fact, that arm7 is not the widest supported architecture. However, the performance is really good in terms of training/usage time.

If I use --user I want to avoid system issues with the python/user versions currently installed on the Pi
If I use --force-reinstall this is mostly due to the fact, that so many libraries force specific dependency versions and I assume a hierarchical order in them. I try to minimize the incompatibility warnings and want to ensure, that the “biggest” library gets its will
If I let you remove a dependency that’s because we previously installed it manually and sometimes there are no symlinks/entries in the site-packages created, however they are importable.

Of course this guide may not work for your specific scenario. Mostly this is because there are so many situations/systems/environments that I can’t cover them all. This guide worked for me even after the third complete reinstall of my Pi so I assume you can either use it directly or getting the idea behind my approach. I am deeply sorry in case I missed a step. I needed 3 full days to work things out and tons of coffee and love of my wife that calmed be down everytime I was on a rampage 😄 So please use my guide and don’t be shy to mention things I might have forgotten.

If there are questions, feel free to ask.

4reactions

TheCedarPrincecommented, Oct 25, 2019

VICTORY!!! 🎉 🎉 🎉

Julian. Julian. JULIAN!!!

WE DID IT!!! @JulianGerhard21 !!! THIS IS HUGE!!!

All I did was the following:

git clone https://github.com/google/dopamine.git
cd dopamine/
sed -i '/opencv-python/d' setup.py
python3.6 -m pip install . --user

And now the bot WORKS!!! I haven’t tested out all the functionality to see if everything is working completely, but it finished training on the RPi completely using spaCy and all the other packages.

Creating Your Own RasaPi - Instructions

@JulianGerhard21 and all others interested in getting RASA on an RPi4, I meticulously created a script that will automatically install everything needed onto your Pi based on the aforementioned exchange:

First, prepare a fresh installation of Raspbian Buster (Lite) on your Pi.
Copy the following script into a file called install.sh

# Update the Raspberry Pi
sudo apt-get update
sudo apt-get upgrade -y 
sudo apt-get dist-upgrade -y

# Install initial build dependencies
# Provides 
# Enables pip3.6 to access pypi
sudo apt-get install libbz2-dev libssl-dev -y 

# Get and install Python3.6
wget https://www.python.org/ftp/python/3.6.8/Python-3.6.8.tar.xz
tar -xvf Python-3.6.8.tar.xz
cd Python-3.6.8
sudo ./configure
sudo make -j4
sudo make install

# Update Python3.6 packages
python3.6 -m pip install --upgrade pip setuptools --user

# Install additional dependencies
# Enables access to Tensorflow whl
# Dependency for the h5py python package
sudo apt-get install python3-pip libhdf5-dev -y

# Install Tensorflow
python3.6 -m pip install tensorflow==1.14.0 --user

# Install OpenCV Dependencies
sudo apt-get install build-essential cmake unzip pkg-config -y
sudo apt-get install libjpeg-dev libpng-dev libtiff-dev -y
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev -y
sudo apt-get install libxvidcore-dev libx264-dev -y
sudo apt-get install libgtk-3-dev -y
sudo apt-get install libcanberra-gtk* -y
sudo apt-get install libatlas-base-dev gfortran -y
sudo apt-get install python3-dev -y

# Download OpenCV and clarify naming scheme
cd ~
wget -O opencv.zip https://github.com/opencv/opencv/archive/4.0.0.zip
wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/4.0.0.zip
unzip opencv.zip
unzip opencv_contrib.zip
mv opencv-4.0.0 opencv
mv opencv_contrib-4.0.0 opencv_contrib

cd ~/opencv
mkdir build
cd build

cmake -D CMAKE_BUILD_TYPE=RELEASE \
    -D CMAKE_INSTALL_PREFIX=/usr/local \
    -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \
    -D ENABLE_NEON=ON \
    -D ENABLE_VFPV3=ON \
    -D BUILD_TESTS=OFF \
    -D OPENCV_ENABLE_NONFREE=ON \
    -D INSTALL_PYTHON_EXAMPLES=OFF \
    -D BUILD_EXAMPLES=OFF ..

# Increasing swap size to make OpenCV
SWAPSIZE=2048
sed -i "s/^CONF_SWAPSIZE.*/CONF_SWAPSIZE=${SWAPSIZE}/" /etc/dphys-swapfile

# Restarting swap service
sudo /etc/init.d/dphys-swapfile stop
sudo /etc/init.d/dphys-swapfile start

# Make OpenCV
make -j4

# Install OpenCV
sudo make install
sudo ldconfig

# Reseting swap size
SWAPSIZE=100
sed -i "s/^CONF_SWAPSIZE.*/CONF_SWAPSIZE=${SWAPSIZE}/" /etc/dphys-swapfile

# Restarting swap service
sudo /etc/init.d/dphys-swapfile stop
sudo /etc/init.d/dphys-swapfile start

# Link cv2 to Python3.6
cd /usr/local/lib/python3.6/site-packages/
sudo ln -s /usr/local/python/cv2/python-3.6/cv2.cpython-36m-arm-linux-gnueabihf.so cv2.so

# In case git is not installed
sudo apt-get install git -y

# Getting codebases for spaCy, tensor2tensor, and RASA
# NOTE: This is hard-coded for rasa-1.4.0 right now - let's make it more elegant soon
cd ~
git clone https://github.com/explosion/spaCy
git clone https://github.com/tensorflow/tensor2tensor
git clone https://github.com/google/dopamine.git
wget https://github.com/RasaHQ/rasa/archive/1.4.0.zip && unzip 1.4.0.zip 

# Installing spaCy
export BLIS_ARCH=generic
cd ~/spaCy
python3.6 -m pip install -r requirements.txt --user
python3.6 setup.py build_ext --inplace
python3.6 -m pip install . --user

# Installing dopamine-rl
cd ~/dopamine
sed -i '/opencv-python/d' setup.py
python3.6 -m pip install . --user

# Installing tensor2tensor
cd ~/tensor2tensor
sed -i '/opencv-python/d' setup.py
python3.6 -m pip install . --user --force-reinstall

# Installing other RASA dependencies
sudo apt install libpq-dev/buster -y 
python3.6 -m pip install psycopg2 --user

# Installing RASA
cd ~/rasa-1.4.0
sed -i '/tensor2tensor/d' setup.py
sed -i '/tensor2tensor/d' requirements.txt
python3.6 -m pip install -r requirements.txt --user --force-reinstall
python3.6 -m pip install . --user --force-reinstall

# Script exit
echo ""
echo ""
echo "------------------------------------------------------------"
echo "Congratulations! Rasa is now installed on your Raspberry Pi."
echo "To test rasa out, run python3.6 -m rasa init and start "
echo "creating your bot!"

Execute the following: sudo chmod +x install.sh
Execute the following: ./install.sh Please note that installation will take a very long time (~3 hours or so). Grab a tea, go for a run, read a book and come back later!
You will have some folders and files leftover in your home directory so feel free to delete those now that everything is installed!

THANK YOU!

I would certainly like to thank @JulianGerhard21 for all the fantastic assistance, input, and massively heavy lifting. Without Julian’s input, none of this would be possible. I have had a wonderful time working together here and learned a lot from you and this process - a “thank you” cannot do you enough justice but… THANK YOU

I would also like to thank @jrosebr for his awesome instructions that I adapted here for installing OpenCV.

Finally, a huge thank you to the RASA team! Thank you for making this wonderful product and I am excited to see how we can all use it on resource-constrained devices!

And with that, I shall now, close the issue. Issue: RESOLVED!

EDIT 10/24/19: Fixed a path error.