Brif is a boilerplate tool based on Docker and FastAPI, designed to streamline the development and deployment of IIIF compliant platforms.

Overview

brif


A boilerplate tool based on Docker, designed to streamline the development and deployment of IIIF compliant platforms.

Embedded with FastAPI, Celery + Rabbit-MQ + Flower, Postgres + PGAdmin, Cantaloupe, Nginx, Bulma.

IIIF features:

  • Cantaloupe image server <=> Image API 2.1
  • FastAPI implementation <=> Presentation API 2.1
  • Automated manifest creation from CSV files
  • IIIF manifests creation based on Prezi
  • Tify viewer directly embedded with each manifest

Content

The tiny dataset and 6 related images used in the demo are released as copyright-free materials, and come from the Finnish National Gallery Open Data platform.

Installation

Backend

You should use the main branch, other branches being used for development purpose.

Fetch all the Git LFS resources: git lfs fetch --all && git lfs pull

You might have to tweak the volumes of the brif_nginx service to import your own certificate provider directory.

You have to create the required nginx configuration files:

  • certificate.json
  • app_docker.conf
  • monitor_docker.conf

Same goes with servers.json if you use the pgadmin container.

Then you're left with creating the .env environment file.

NB: For all these required files, you'll find xxxxxx.example sample files ready to adapt.


Cantaloupe

Mount your images as volumes in the cantaloupe service and set FilesystemSource.BasicLookupStrategy.path_prefix in cantaloupe.properties accordingly to get things going. From there, you can easily set your logs, enable/disable different API version number (i.e. from to 3) as it follows the very official documentation.


Frontend

You can add your own head_meta.html , or discard it from base.html while implementing up the {title} tag again.


Data

You just need to copy your datasets in data/input, and the dashboard should automatically pick them up.

Or change accordingly in docker's x-brif-common

Each directory can contain multiple datasets, and they will be treated separately. Each directory can have only 1 specific mapping.

Each directory can contain one mapping.json file to implement a specific mapping for the data pipeline. If not present, a default mapping will be applied.


Run

Only the core containers

docker-compose docker-compose.core.yml up

+ monitoring containers

docker-compose -f docker-compose.core.yml -f docker-compose.monitoring.yml up

+ with Brif app (including test container)

docker-compose -f docker-compose.core.yml -f docker-compose.monitoring.yml -f docker-compose.brif.yml up

+ with Nginx containers (tagged with 'prod_live' profile)

docker-compose -f docker-compose.core.yml -f docker-compose.monitoring.yml -f docker-compose.brif.yml --profile live_prod up

Docker is great but sometimes tricky ... when changes are made, don't forget to:

  • Use the --build flag.
  • Cleanse the database properly by using the prune and rm tools to purge volumes and containers.

Manual

Instructions

This tool is not meant to search within the collection, only to transform the raw data into valid IIIF manifests.

To browse further the collection you will probably need to import the transformed data into a search engine such as Elasticsearch or Solr.

Each transformed dataset comes with a new collection dataset which gathers all the transformed IIIF manifests URLs, thus making it easy to import the related data within your system.


Docs & Monitoring

You can find the Swagger UI for the whole tool at the /docs url. Some endpoints are voluntarily not presented there, look for include_in_schema=False for the exclusions if necessary.

The tool comes with optional monitoring services (Flower and PGAdmin) to monitor further your Postgres database and the tasks going through the pipeline.


Dashboard UI

At startup, a dashboard is directly accessible at the url /dashboard

  • The dashboards is a basic UI to manage your datasets and check the transformed collections.
  • It shows some stats, along with sample links.

The workflow is relatively simple:

  • The whole dataset is itemised.
  • A dedicated IIIF Image API is spinned up based on the provided images.
  • Each new item/record is transformed into a IIIF manifest.
  • A new collection dataset is created which gathers all the IIIF manifests urls.

Once processed, all manifests can be accessed with their base URI followed by /manifest.json to access the data or either /view for the Tify viewer.


Development

If you want to make some changes in this repo while following the same environment tooling.

poetry config virtualenvs.in-project true
poetry install && poetry shell
pre-commit install
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