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, Bulma
and provided with an example configuration for Nginx.
NB: This tool is not actively maintained annd you might encounter some issues during the docker compose build phase.
Overall, it's mostly a matter of dependencies to update and some Dockerfiles to refine.
- 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
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.
You should use the main branch, other branches being used for development purpose.
Fetch all the Git LFS resources: git lfs install && git lfs fetch --all && git lfs pull
If you want to use Nginx, you can just create a symbolic link
from setup/all_containers.conf to the Nginx websites directories in /etc/nginx/sites-* in your machine, and tweak the the provided example configuration with the correct Docker containers IPs
and relevant references to your certificates.
From the repository root, use this command to retrieve these IPs:
docker compose ps -q | xargs docker inspect -f '{{.Name}} - {{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}'
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.
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.
You can add your own head_meta.html, or discard it from base.html while implementing up the {title} tag again.
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.
To check your installation, run the following command.
docker-compose docker-compose.yml api_test up
NB: You will need to import the provided data and image samples for all the tests to pass. See in Section for further details.
Only the main containers
docker-compose up
+ monitoring containers
docker-compose -f docker-compose.yml -f docker-compose.monitoring.yml up
+ with Brif app (including test container)
docker-compose -f docker-compose.yml -f docker-compose.monitoring.yml up
Docker is great but sometimes tricky ... when changes are made, don't forget to:
- Use the
--buildflag. - Cleanse the database properly by using the
pruneandrmtools to purge volumes and containers.
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.
To make it easier to test this tool in action, we included both data and image samples.
You should import them in the locations you for chose these elements,
which can be set up via the paramenters DATA_DIR and CONTENT_DIR in the .env file.
Find the files in the setup directory:
setup/app/input_sample/test_dataset/test_records.csvsetup/cantaloupe/test_images.zip
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.
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.
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