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License: GPL v2 CodeFactor Build Status Docs

COLLABORATION SYSTEM

The system allows individual users to form communities, create groups, participate in various activities defined in the community/group, and thus, enhance its value for the society in terms of education.

Requirements and Django Packages

For development installation (Virtual Environment)

  1. Install virtualenv

    	sudo pip3 install virtualenv 
  2. Clone the project from github

    	git clone https://github.com/fresearchgroup/Collaboration-System.git 
  3. Create a virtual env ---

     	virtualenv collab -p python3 
  4. Activate the virtual environment --

    	source collab/bin/activate
  5. Install the requirements.txt --

    	pip3 install -r Collaboration-System/requirements.txt
  6. Install mysql server --

    	$ sudo apt-get update
    	
    	$ sudo apt-get install mysql-server
    
    	$ sudo apt-get install libmysqlclient-dev
    
        $ mysql -u root -p
    
        Enter password=root
    	
    mysql> create database collaboration;
        mysql> use collaboration;
        mysql> source collab.sql   
    
  7. Create a .env inside CollaborationSystem and paste the following -

       		sudo nano .env
        SECRET_KEY=myf0)*es+lr_3l0i5$4^)^fb&4rcf(m28zven+oxkd6!(6gr*6
        DEBUG=True
        DB_NAME=collaboration
        DB_USER=root
        DB_PASSWORD=root
        DB_HOST=localhost
        DB_PORT=3306
        ALLOWED_HOSTS= localhost
        GOOGLE_RECAPTCHA_SECRET_KEY=6Lfsk0MUAAAAAFdhF-dAY-iTEpWaaCFWAc1tkqjK
        EMAIL_HOST=localhost
        EMAIL_HOST_USER=
        EMAIL_HOST_PASSWORD=
        EMAIL_PORT=25
        EMAIL_USE_TLS=False
        [email protected]
        SOCIAL_AUTH_GOOGLE_OAUTH2_KEY=735919351499-ajre9us5dccvms36ilhrqb88ajv4ahl0.apps.googleusercontent.com
        SOCIAL_AUTH_GOOGLE_OAUTH2_SECRET=I1v-sHbsogVc0jAw9M9Xy1eM
    	LOG_TYPE=TOSERVER
    	LOG_PROTOCOL=http
    	LOG_ADDRESS=logstash
    	LOG_PORT=5000
    	LOG_STORE=debug.log
    	LOG_USE_PROXY=False
    	URL_BASIC=http://localhost:8000/
    	PAGE_SIZE=1000
    	MAX_PAGE_SIZE=10000
    	EVENTAPI_TOKEN_USERNAME=eventloguser
    	EVENTAPI_TOKEN_PASSWORD=eventlogpass
    	EVENT_API_TOKEN=
    	ELASTICSEARCH_ADDRESS=
    	
    	NODESERVERURL=http://localhost
    	NODESERVERPORT=9001
    	COLLAB_ROOT=http://localhost:7000
    	H5P_ROOT=http://localhost:8000
    	APIKEY=ae0135343b703000e7377f8438e5f1154dcdc2ffc434268729203764cfe28b26
    
  8. Do all the migrations --

    	python3 manage.py migrate
  9. Runserver --

    	python3 manage.py runserver

For manual installtion -- https://fresearchgroup.github.io/docs-collaboration-system/

For automated installation using nginx and gunicorn- https://github.com/abhisgithub/django-nginx-installation-script

For development installation (Docker) -

-- Install Docker and Docker-Compose from --

    Docker - https://docs.docker.com/install/linux/docker-ce/ubuntu/#set-up-the-repository

    Docker Compose -- https://docs.docker.com/compose/install/
  1. Clone the repository --
   	git clone https://github.com/fresearchgroup/Collaboration-System.git
  1. The run the following commands inside the repository --

    
    	docker-compose build
    
    	docker-compose up db
    
     	docker exec -i <container-image-name> mysql -u<username> -p<password> django < collab.sql
    
    	docker-compose run web python manage.py migrate
    
    	docker-compose run web python manage.py createsuperuser
    
    	docker-compose run web python manage.py loaddata workflow roles faq
    
    	docker-compose up
    

Event Logging

To set-up event logging for this system, please refer to the installation steps given in the repository link given below: https://github.com/fresearchgroup/Collaboration-System-Event-Logs

Interactive Content (H5P) and Real-time editing

To create and edit interactive content (H5P) and to enable real-time collaborative editing of articles, please refer to the installation steps given in the repository link given below: https://github.com/fresearchgroup/Community-Content-Tools

Recommendation System

This system is used to recommend articles based on his/her activity in the sytem. Please refer to the installation steps given in the repository below: https://github.com/fresearchgroup/Community-Recommendation

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