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A visual text analytics system for Debriefing reflection essays

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EssayIQ

  • Settings are identical to Conceptvector. The followings are copied from Conceptvector.

Procedure to deploy EssayIQ in Digital Ocean.

Setting up the environment:

1. Install Anaconda

  • Download the latest distribution

    wget https://repo.continuum.io/archive/Anaconda2-5.3.0-Linux-x86_64.sh 
    
  • Execute the script

    bash Anaconda2-5.3.0-Linux-x86_64.sh
    

2. Create a custom environment

  • Create a conda environment 'conceptvector'
    conda create -n conceptvector python=2.7 anaconda
    
  • Activate the conda environment
    source activate conceptvector
    pip install -r requirements.txt
    

3. Install uwsgi

conda install -c travis uwsgi

4. Install flask

conda install -c https://conda.anaconda.org/anaconda flask

5. Cloning the source code

git clone https://github.com/intuinno/conceptvector.git

6. Install npm, bower & grunt

sudo apt install npm
sudo  npm install -g bower
sudo  npm install -g grunt

Setting up the client

  • Change the directory to conceptvector/client
  • Build client
    npm install
    bower install
    grunt build
    
  • Run client
    grunt serve
    

Setting up the server

  1. Activate conceptvector environment

    source activate conceptvector
    
  2. Install dependencies

    • Install flask-migrate, flask-bcrypt, flask-restful, flask-cors, marshmallow, ipdb, psycopg2, flask-sqlalchemy
      conda install -c conda-forge flask-migrate flask-bcrypt flask-restful flask-cors marshmallow ipdb psycopg2 flask-sqlalchemy
      
    • Install flask-script
      pip install Flask-Script
      
  3. Setting up environment variables

    • Create the following files

      cd ~/anaconda2/envs/conceptvector/
      mkdir -p ./etc/conda/activate.d
      mkdir -p ./etc/conda/deactivate.d
      
      touch ./etc/conda/activate.d/env_vars.sh
      touch ./etc/conda/deactivate.d/env_vars.sh
      
    • Add the following content to both the files (env_vars.sh)

      export APP_SETTINGS=config.DevelopmentConfig
      export DATABASE_URL=postgresql://postgres:postgres@localhost/conceptvectorDB
      
  4. Download & unzip stanford glove dataset

    • Change the directory to conceptvector/server
    mkdir data
    cd data
    wget http://nlp.stanford.edu/data/glove.6B.zip
    unzip glove.6B.zip
    
  5. Set up database

    • Install PostgreSQL database
      sudo apt install postgresql postgresql-contrib
      
    • Start the databse service
      sudo service postgresql start
      
    • Create a database conceptvectorDB using the default user postgres
      sudo -u postgres createdb conceptvectorDB
      
    • Upgrade the database
      • change the directory to conceptvector/server & run the following command
      python manage.py db upgrade
      
    • At this stage, you should be able to connect to database by following
       psql conceptvectorDB postgres
      
  6. Test the server

    • Activate conceptvector environment
      source activate conceptvector
      
    • Change the directory to conceptvector/server & run the following command
      python manage.py runserver
      
      

Setup with Docker compose

Requirements

  • Docker >= 18.06
  • docker-compose >= 1.22

How to run local server

  1. Clone repository
git clone https://github.com/intuinno/conceptvector.git
  1. Run with docker-compose
cd conceptvector
docker-compose up

Now you can access to local dev server:

http://localhost:9000 for frontend, http://localhost:5000 for backend.

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