That's it. You should be good to go and run the master script now.
That's it for R. Run the master script and then go ahead to **Bot Setup** to install and run the rasa bot.
## Manual installation
...
...
@@ -169,26 +169,28 @@ R CMD INSTALL wikiproc_<version>.tar.gz
```
That's it. You should be good to go and run the master script now.
=======
## 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
```
```{bash}
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
```
```{bash}
pip install rasa_nlu
pip install rasa_core
```
Install the pipeline
```
```{bash}
pip install sklearn_crfsuite
pip install spacy
...
...
@@ -198,17 +200,17 @@ python -m spacy link en_core_web_md en
Now you can train and run the bot
```
```{bash}
cd rasa/
make train
```
```
```{bash}
make run
```
Run in [Debug Mode](https://rasa.com/docs/core/debugging/) for more logging
This repository contains all files required to download data from Wikipedia, process that data to extract facts about physicists and build a chatbot based on the rasa framework with that information.
### Prerequisites
The R script assumes all the packages in the `packages.list` file are installed within R. You may do this with:
Furthermore you will need to have an spacy installation with the english language data installed. By default the script will assume to find this in a conda environment named `spcy`, if you need to change that do so in the `Master.R` file.
To build the **wikiproc** package navigate to the processing directory and run:
```bash
R CMD build wikiproc
R CMD INSTALL wikiproc_<version>.tar.gz
```
_Note: This will require the [R Tools](https://cran.r-project.org/bin/windows/Rtools/) on windows and possibly additional packages on *nix platforms._
To run the rasa bot rasa will need to be installed. It is recommended to do that in a conda environment, you may create one with:
```{bash}
conda create -n rasa_env python=3.6.7
source activate rasa_env
```
In this environment install rasa_nlu, rasa_core, sklean_crfsuite and spacy. Also download the spacy en_core_web_md language data.
```{bash}
pip install rasa_nlu
pip install rasa_core
pip install sklearn_crfsuite
pip install spacy
python -m spacy download en_core_web_md
python -m spacy link en_core_web_md en
```
### Running
The data processing side is done by the `Master.R` script in the `processing/script` folder. The script assumes the working direcory to be somewhere within the base directory `wiki-rasa` so make sure to either call `Rscript` from within this directory or to set the working directory in R here prior to sourcing. Easiest way is to call the script from the base directory of the repository:
```{bash}
Rscript processing/script/Master.R
```
This will download the required data, process it and generate the data file required for the chat bot. After that train the bot (don't forget to activate the conda environment if you're using one).
```{bash}
cd rasa/
make train
```
You're ready to run the bot.
```{bash}
make run
```
### Installing on debian
For a detailed guide on installing on a Debian 9 machine take a look at [Installation](INSTALL.md).
### Building the docker
**_Work in progress_**
Run the build script for your system, e.g. on Windows `build_docker.bat` or `build_docker.sh` on Linux.
After that you should be good to start the docker with
_Note: This will do all processing including data download in the docker container and thus results in a rather large container.
Container size will be reduced in the future_
```{bash}
docker run -it chatbot
```
## Contributing
Before merging please make sure to check the following:
...
...
@@ -32,38 +113,3 @@ When writing a function to extract a feature use the following as guidelines:
* If your function is to be visible from the outside, make sure to add `@export` to the roxygen comment
* Set the working directory to `wikiproc` and call `devtools::document()`
* Step into `processing` and use `devtools::install("wikiproc")` to install the package
## Installation
You may use this software by installing the **wikiproc** package and then running the `master.R` script. There are also directions on how to install from scratch on a debian vm and on how to build a docker.
### General prerequisites
The script assumes all the packages in the `packages.list` file are installed within R. Furthermore you will need to have an spacy installation with the english language data installed. By default the script will assume to find this in a conda environment named `spcy`, if you need to change that do so in the `ProcessNER.R` file.
To build the **wikiproc** package navigate to the processing directory and run:
```bash
R CMD build wikiproc
R CMD INSTALL wikiproc_<version>.tar.gz
```
_Note: This will require the [R Tools](https://cran.r-project.org/bin/windows/Rtools/) on windows and possibly additional packages on *nix platforms._
The data processing side is done by the `Master.R` script in the `r` folder. This may be called via `Rscript r/Master.R` from any command line or via `source("r/Master.R")` from within R. The script assumes the working direcory to be the base directory `wiki-rasa` so make sure to either call `Rscript` from within this directory or to set the working directory in R here prior to sourcing.
### Installing on debian
For a detailed guide on installing on a Debian 9 machine take a look at [Installation](docs/install_debian.md).
### Building the docker
**_Work in progress_**
Run the build script for your system, e.g. on Windows `build_docker.bat` or `build_docker.sh` on Linux.
After that you should be good to start the docker with
