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# Install instructions
This provides instructions for seting up the software on a freshly installed debian 9 system. It will most likely work on any recent ubuntu system too, though there may be some hickup with the python versions.
## Installing Debian
This assumes a standard install of debian was made using the [smallcd AMD64](https://www.debian.org/distrib/netinst#smallcd) debian image. It was tested selecting only the base system with the standard system utilities (which contain python) and no gui.
This guide assumes during setup a user named rasa was created, though this shouldn't be too hard to adapt to.
### Hypervisor specific steps
#### Hyper-V
Nothing to do, works out of the box.
#### KVM
Not tested.
#### VirtualBox
Works.
## Installing sudo
Though not required we'll make rasa a sudoer for convenience reasons.
First log in as root and run
```shell
apt-get install sudo
```
Next we'll make the `rasa` user a sudoer
```shell
usermod -aG sudo rasa
```
All done here. `exit` and log in as rasa.
## Seting up python for cleanNLP
Just to make sure we update the system with. We'll also need gcc nad git, so go ahead and install em.
```shell
sudo apt-get update && sudo apt-get dist-upgrade -y && sudo apt-get install gcc git build-essential python-dev -y
```
Next, install miniconda:
```shell
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x84_64.sh
```
Defaults are fine here.
Log out and back in.
Now we create an environment for spacy and install it:
```shell
conda create -n spcy python=3
conda activate spcy
pip install spacy
python -m spacy download en
conda deactivate
```
## Installing R
_There is a script that will do all these things for you. If you want to use it skip ahead to **Cloning the project** and be sure to execute the script as described there_
We need to add the cran repository to sources.list as the r packages in the debian repositories are somewhat out of date.
For that we'll need a few packages
```shell
sudo apt install dirmngr --install-recommends
sudo apt install software-properties-common apt-transport-https -y
```
Now we'll add the key for the cran ppa and add the ppa
```shell
sudo apt-key adv --keyserver keys.gnupg.net --recv-key 'E19F5F87128899B192B1A2C2AD5F960A256A04AF'
sudo add-apt-repository 'deb https://cloud.r-project.org/bin/linux/debian stretch-cran35/'
```
Finally we may install R
```shell
sudo apt-get update
sudo apt-get install r-base-dev
```
While we're at it, we install a few more things we need for some R packages and also git.
```shell
sudo apt-get install libcurl4-openssl-dev libssl-dev libxml2-dev git -y
```
## Cloning the project
Run:
```shell
git clone https://git.informatik.uni-leipzig.de/text-mining-chatbot/wiki-rasa.git
cd wiki-rasa
```
_If skipping the steps above run the install script now._
```shell
./install.sh
```
## Installing R Packages
This needs to be done from an Interactive R console as R will ask wheather to use an personal library the first time installing packages. To do this, open R and type the following:
```r
install.packages(readLines("packages.list"))
```
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This will install all the packages required. When asked if you want to use a personal library say yes and accept the defaults.
## Bot Setup
In order to setup and run the [Rasa Bot](https://rasa.com/docs/) we recommend to use a [conda](https://conda.io/docs/user-guide/getting-started.html#managing-environmentsß) environment again with Python 3.6.7
```
conda create -n rasa_env python=3.6.7
source activate rasa_env
```
You need to install [Rasa Core](https://rasa.com/docs/core/installation/) and [Rasa NLU](https://rasa.com/docs/nlu/installation/) to run the Bot
```
pip install rasa_nlu
pip install rasa_core
```
Install the pipeline
```
pip install sklearn_crfsuite
pip install spacy
python -m spacy download en_core_web_md
python -m spacy link en_core_web_md en
```
Now you can train and run the bot
```
cd rasa/
make train
```
```
make run
```
Run in [Debug Mode](https://rasa.com/docs/core/debugging/) for more logging
```
make run-debug
```