- Visual Studio Code or other IDE
- Python 3.7
- git clone
git clone https://github.com/fzi-forschungszentrum-informatik/dam4kmu.git
-
install NodeJs from https://nodejs.org/en/download/ (make sure
npmis included) -
For Windows: add the NodeJs path to the user's environment variable
PATH; e.g.
C:\Program Files\nodejs\
- Unzip following files (using 7zip, the file fragments will be assembled automatically)
DAM4KMU\backend\nlp_backend\NER_Large\vocab\vectors
DAM4KMU\backend\nlp_backend\germanwordembeddings.model
- Installing dependencies for python and nodejs
// change into the repository's root folder
cd dam4kmu
// Create new folder name node_modules
mkdir node_modules
// Install the Nodejs dependencies from package.json
npm install
// Create python virtualenv name `env`
python -m venv ./env
// Activate the venv
source ./env/bin/activate
// Install the python dependencies
python -m pip install -r requirements.txt
- Initiate the django database
// go to the folder containing the file `manage.py`
cd DAM4KMU
// and run
python manage.py migrate
python manage.py makemigrations
- Run the program
// run Django server
python manage.py runserver
// launch another console at the repository's root and run React or Nodejs
npm run dev
We use as a backbone for our Research Assistant a Google Custom Search with a free limit of 10000 queries per day.
Please create your own api_key and cse_id based on the following steps:
- Get a custom search engine API key (api_key)
– Go to https://developers.google.com/custom-search/v1/introduction and click 'Get a Key'.
– Click 'Select or create project'.
– Click 'Create new project'.
– Enter a new project name. Click 'Next'.
– Copy api key to clipboard.
- Get a custom search engine id (cse_id)
– Go to https://programmablesearchengine.google.com/about/ and click 'Get started'.
– Click 'Add' to add a new search engine.
– Use 'www.example.com' as a dummy for the 'Sites to search' field.
– Select 'German' as language.
– Give the search engine a name.
– Click 'Create'.
– Go back to the search engine overview page. Click on your created search engine.
– Delete 'www.example.com' from 'Sites to search'.
– Copy search engine id to clipboard.
Insert api_key and cse_id in DAM4KMU/DAM4KMU/settings.py in line 160/161.
This software is licensed under the MIT license, which can be found in the file LICENSE.
All dependencies are copyright to the respective authors and released under the licenses listed in LICENSE_LIBRARIES.
This software was developed at the FZI Research Center for Information Technology.
The associated research is partially funded by the German Ministry of Education and Research (BMBF) (grant number: 01IS18086) within the context of the project DAM4KMU.
