uwazi

uwazi

Uwazi is a web-based, open-source solution for building and sharing document collections

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Uwazi is a flexible database application designed for capturing and organizing collections of information, with a focus on document management. It is developed and supported by HURIDOCS, benefiting human rights organizations globally. The tool requires NodeJs, ElasticSearch, ICU Analysis Plugin, MongoDB, Yarn, and pdftotext for installation. It offers production and development installation guides, including Docker setup. Uwazi supports hot reloading, unit and integration testing with JEST, and end-to-end testing with Nightmare or Puppeteer. The system requirements include RAM, CPU, and disk space recommendations for on-premises and development usage.

README:

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Uwazi CI Maintainability Test Coverage

Uwazi is a flexible database application to capture and organise collections of information with a particular focus on document management. HURIDOCS started Uwazi and is supporting dozens of human rights organisations globally to use the tool.

Uwazi | HURIDOCS

Read the user guide

Installation guide

Dependencies

Before anything else you will need to install the application dependencies:

Production

Install/upgrade procedure

Development

If you want to use the latest development code:

$ git clone https://github.com/huridocs/uwazi.git
$ cd uwazi
$ yarn install
$ yarn blank-state

If you want to download the Uwazi repository and also download the included git submodules, such as the uwazi-fixtures, which is used for running the end-to-end testing:

$ git clone --recurse-submodules https://github.com/huridocs/uwazi.git
$ cd uwazi
$ yarn install

If the main Uwazi repository had already been cloned/downloaded and now you want to load its sub-modules, you can run

$ git submodule update --init

There may be an issue with pngquant not running correctly. If you encounter this issue, you are probably missing the library libpng-dev. Please run:

$ sudo rm -rf node_modules
$ sudo apt-get install libpng-dev
$ yarn install

Docker

Infrastructure dependencies (ElasticSearch, ICU Analysis Plugin, MongoDB, Redis and Minio (S3 storage) can be installed and run via Docker Compose. ElasticSearch container will claim 2Gb of memory so be sure your Docker Engine is alloted at least 3Gb of memory (for Mac and Windows users).

$ ./run start

Development Run

$ yarn hot

This will launch a webpack server and nodemon app server for hot reloading any changes you make.

Webpack server

$ yarn webpack-server

This will launch a webpack server. You can also pass --analyzeto get detailed info on the webpack build.

Testing

Unit and Integration tests

We test using the JEST framework (built on top of Jasmine). To run the unit and integration tests, execute

$ yarn test

This will run the entire test suite, both on server and client apps.

Some suites need MongoDB configured in Replica Set mode to run properly. The provided Docker Compose file runs MongoDB in Replica Set mode and initializes the cluster automatically, if you are using your own mongo installation Refer to MongoDB's documentation for more information.

End to End (e2e)

For End-to-End testing, we have a full set of fixtures that test the overall functionality. Be advised that, for the time being, these tests are run ON THE SAME DATABASE as the default database (uwazi_developmet), so running these tests will DELETE any existing data and replace it with the testing fixtures. DO NOT RUN ON PRODUCTION ENVIRONMENTS!

Running end to end tests requires a running Uwazi app.

Running tests with Nightmare

$ yarn hot

On a different console tab, run

$ yarn e2e

Running tests with Puppeteer

$ DATABASE_NAME=uwazi_e2e INDEX_NAME=uwazi_e2e yarn hot

On a different console tab, run

$ yarn e2e-puppeteer

Note that if you already have an instance running, this will likely throw an error of ports already been used. Only one instance of Uwazi may be run in the same port at the same time.

Default login

The application's default login is admin / change this password now

Note the subtle nudge ;)

System Requirements

  • For big files with a small database footprint (such as video, audio and images) you'll need more HD space than CPU or RAM
  • For text documents you should consider some decent RAM as ElasticSearch is pretty greedy on memory for full text search

The bare minimum you need to be able to run Uwazi on-prem without bottlenecks is:

  • 4 GB of RAM (reserve 2 for Elastic and 2 for everything else)
  • 2 CPU cores
  • 20 GB of disk space

For development:

  • 8GB of RAM (depending on whether the services are running)
  • 4 CPU cores
  • 20 GB of disk space

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