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Metadata Catalogue API

!!! note

This page was the old readme. Re-organizing and updating it into our structured documentation
pages is work in progress. This page will serve as an overview page that serves as a 
"getting started" page and quick reference, with references to pages with in-depth information.

This repository contains the AI on Demand (AIoD) REST API. It is built with FastAPI that interacts with a database (MySQL) and OpenML's REST API. Both the database and the REST API are run from docker in separate containers.

The AIoD REST API will allow any kind of service to interact with the AIoD portal to discover, retrieve, and share AI resources. It forms the connection between user-facing components, such as the AIoD website or Python Client API, and the backend. The metadata for datasets, models and other resources can be accessed, added, updated and deleted through this API.

Architecture

All metadata is stored in the AIoD metadata database. For every instance of the API (there will be multiple running instances, for reliability and performance), an instance of this database will run on the same machine (on the same node). The type of database is not yet determined, for now we use a simple MySQL database.

The metadata is stored in AIoD format. When the user requests an item, such as a dataset, it can be returned in AIoD format, or converted to any supported format, as requested by the user. For datasets, we will for instance support schema.org and DCAT-AP.

Requesting a dataset will therefore be simply:

Get dataset UML

To fill the database, a synchronization process must be running continuously for every platform (e.g. HuggingFace or OpenML). This synchronization service of a platform will be deployed at a single node. The synchronization service queries its platform for updates, converts the metadata to the AIoD format and updates the database.

Note that this synchronization process between the platform and the database, is different from the synchronization between database instances. The latter is under discussion in the AIoD Synchronization Meetings.

Prerequisites

For development:

  • Python3.11 with python3.11-dev (sudo apt install python3.11-dev on Debian)
  • Additional 'mysqlclient' dependencies. Please have a look at their installation instructions.

Production environment

For production environments elasticsearch recommends -Xss4G and -Xmx8G for the JVM settings.
This parameters can be defined in the .env file. See the elasticsearch guide.

For Keycloak, the --http-enabled=true and --hostname-strict-https=false should be omitted from the docker-compose file.

Installation

This repository contains two systems; the database and the REST API. As a database we use a containerized MySQL server (through Docker), the REST API can be run locally or containerized. Information on how to install Docker is found in their documentation.

Using docker compose

docker compose --profile examples up -d

starts the MYSQL Server, the REST API, Keycloak for Identity and access management and Nginx for reverse proxying.
Once started, you should be able to visit the REST API server at: http://localhost and Keycloak at http://localhost/aiod-auth
To authenticate to the REST API swagger interface the predefined user is: user, and password: password
To authenticate as admin to Keycloak the predefined user is: admin and password: password
To use a different DNS hostname, refer to the "Changing the configuration" section below for instructions on how to ovverride HOSTNAME in .env and opendid_connect_url in config.toml.
This configuration is intended for development, DO NOT use it in production.

To turn if off again, use

docker compose --profile examples down

To connect to the database use ./scripts/database-connect.sql.

mysql> SHOW DATABASES;
+--------------------+
| Database           |
+--------------------+
| information_schema |
| mysql              |
| performance_schema |
| sys                |
+--------------------+
4 rows in set (0.03 sec)

Now, you can visit the server from your browser at localhost:8000/docs.

Changing the configuration

You may need to change the configuration locally, for example if you want different ports to be used. Do not change files, instead add overrides.

Docker Compose

For docker compose, the environment variables are defined in the .env file. To override variables, for example AIOD_LOGSTASH_PORT, add a new file called override.env:

AIOD_LOGSTASH_PORT=5001

Then also specify this when you invoke docker compose, e.g.: docker compose --env-file=.env --env-file=override.env up Note that order is important, later environment files will override earlier ones. You may also use the ./scripts/up.sh script to achieve this (see "Shorthands" below).

Config.toml

The main application supports configuration options through a toml file. The defaults can be found at src/config.default.toml. To override them, add a src/config.override.toml file. It follows the same structure as the default file, but you only need to specify the variables to override.

Using connectors

You can specify different connectors using

docker compose --profile examples --profile huggingface-datasets --profile openml --profile zenodo-datasets up -d
docker compose --profile examples --profile huggingface-datasets --profile openml --profile zenodo-datasets down

Make sure you use the same profile for up and down, or use ./scripts/down.sh (see below), otherwise some containers might keep running.

Shorthands

We provide two auxiliary scripts for launching docker containers and bringing them down. The first, ./scripts/up.sh invokes docker compose up -d and takes any number of profiles to launch as parameters. It will also ensure that the changes of the configurations (see above) are observed. If USE_LOCAL_DEV is set to true (e.g., in override.env) then your local source code will be mounted on the containers, this is useful for local development but should not be used in production. E.g., with USE_LOCAL_DEV set to true, ./scripts/up.sh resolves to: docker compose --env-file=.env --env-file=override.env -f docker-compose.yaml -f docker-compose.dev.yaml --profile examples up -d

The second script is a convenience for bringing down all services, including all profiles: ./scripts/down.sh

Local Installation

If you want to run the server locally, you need Python 3.11. We advise creating a virtual environment first and install the dependencies there:

python3.11 -m venv venv
source venv/bin/activate
python -m pip install .

For development, you will need to install the optional dependencies as well:

source venv/bin/activate
python -m pip install ".[dev]"

Moreover, you are encouraged to install the pre-commit hooks, so that black, mypy and the unittests run before every commit:

pre-commit install

You can run

pre-commit run --all-files

To run pre-commit manually.

After installing the dependencies you can start the server. You have 3 options:

  1. Run from your machine:
cd src
python main.py --reload

The --reload argument will automatically restart the app if changes are made to the source files. 2. Run using docker. For instance using scripts/run_apiserver.sh 3. Run using DevContainer (see next subsection)

Authentication

Currently, the code is by default running using the local Keycloak. To make this work, you need to set an environment variable. You can do this by setting the KEYCLOAK_CLIENT_SECRET in src/.env.

# src/.env
KEYCLOAK_CLIENT_SECRET=[SECRET]

Alternatively, you can connect to a different keycloak instance by modifying src/.env. EGI Checkin can for instance be used on a deployed instance - not on local host. Marco Rorro is the go-to person to request the usage of the EGI Checkin.

The reason that EGI Checkin doesn't work on localhost, is that the redirection url of EGI Checkin is strict - as it should be. On our development keycloak, any redirection url is accepted, so that it works on local host or wherever you deploy. This should never be the case for a production instance.

See authentication README for more information.

Creating the Database

By default, the app will create a database on the provided MySQL server. You can change this behavior through the build-db command-line parameter, it takes the following options:

  • never: never creates the database, not even if there does not exist one yet. Use this only if you expect the database to be created through other means, such as MySQL group replication.
  • if-absent: Creates a database only if none exists. (default)
  • drop-then-build: Drops the database on startup to recreate it from scratch. THIS REMOVES ALL DATA PERMANENTLY. NO RECOVERY POSSIBLE.

Populating the Database

To populate the database with some examples, run the connectors/fill-examples.sh script. When using docker compose you can easily do this by running the "examples" profile: docker compose --profile examples up

Usage

Following the installation instructions above, the server may be reached at 127.0.0.1:8000. REST API documentation is automatically built and can be viewed at 127.0.0.1:8000/docs.

Automatically Restart on Change

If you want to automatically restart the server when a change is made to a file in the project, use the --reload parameter. It is important to realize that this also re-initializes the connection to the database, and possibly will do any start-up work (e.g., populating the database).

Database Structure

The Python classes that define the database tables are found in src/database/model/. The structure is based on the metadata schema.

Adding resources

See src/README.md.

Backups and Restoration

We provide several scripts to facilitate the scheduling of backups and the manual restoration of files. For details on these scripts and others, please see scripts/README.md.

Releases