Quick Start
Antenna uses Docker & Docker Compose to run all services locally for development.
1) Install Docker for your host operating (Linux, macOS, Windows)
2) Add the following to your /etc/hosts
file in order to see and process the demo source images. This makes the hostname minio
and django
alias for localhost
so the same image URLs can be viewed in the host machine's web browser and be processed by the ML services. This can be skipped if you are using an external image storage service.
127.0.0.1 minio
127.0.0.1 django
2) The following commands will build all services, run them in the background, and then stream the logs.
docker compose up -d
docker compose logs -f django celeryworker ui
# Ctrl+c to close the logs
3) Optionally, run additional ML processing services: processing_services
defines ML backends which wrap detections in our FastAPI response schema. The example
app demos how to add new pipelines, algorithms, and models. See the detailed instructions in processing_services/README.md
.
docker compose -f processing_services/example/docker-compose.yml up -d
# Once running, in Antenna register a new processing service called: http://ml_backend_example:2000
4) Access the platform the following URLs:
- Primary web interface: http://localhost:4000
- API browser: http://localhost:8000/api/v2/
- Django admin: http://localhost:8000/admin/
- OpenAPI / Swagger documentation: http://localhost:8000/api/v2/docs/
A default user will be created with the following credentials. Use these to log into the web UI or the Django admin.
- Email:
antenna@insectai.org
- Password:
localadmin
5) Stop all services with:
$ docker compose down
Development
Install the pre-commit tool to run linting & formatting checks before each git commit. It's typical to install this tool using your system-wide python.
pip install pre-commit # Install pre-commit system-wide
pre-commit install # Install the hook for our project
If using VS Code, install the formatting extensions that are automatically suggested for the project (e.g. black). Format-on-save should be turned on by default from the project's vscode settings file.
Frontend
Dependencies
Configuration
By default this will try to connect to http://localhost:8000 for the backend API. Use the env var API_PROXY_TARGET
to change this. You can create multiple .env
files in the ui/
directory for different environments or configurations. For example, use yarn start --mode staging
to load .env.staging
and point the API_PROXY_TARGET
to a remote backend.
Installation
Note: if you installed the ui using Docker first (as instructed in the quick-start) then your local node_modules/
directory will be owned by root. Change the permissions with:
sudo chown -R ${UID}:${UID} ui/node_modules
. The version of Node on your host machine must match that of the Docker container (which will be the case if you follow the nvm
instructions below.)
# Enter into the ui directory
cd ui
# Install Node Version Manager
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
# Install required Node.js version
nvm install
# Install Yarn dependencies
yarn install
# Start the frontend
yarn start
Visit http://localhost:3000/
Backend
Dependencies
All backend packages are installed in the docker containers, however for faster auto-completion and intellisense, you can install them on the host machine:
python -m venv venv
source venv/bin/activate
pip install -r requirements/local.txt
Helpful Commands
Run the docker compose stack in the background
docker compose up -d
Watch the logs of Django & the backend workers
docker compose logs -f django celeryworker
Watch the logs of all services:
docker compose logs -f
Create a super user account:
docker compose run --rm django python manage.py createsuperuser
Create a fresh demo project with synthetic data
docker compose run --rm django python manage.py create_demo_project
Run tests
docker compose run --rm django python manage.py test
Run tests with a specific pattern in the test name
docker compose run --rm django python manage.py test -k pattern
Run tests and drop into interactive shell on failure
docker compose run --rm django python manage.py test -k pattern --failfast --pdb
Speed up development of tests by reusing the db between test runs
docker compose run --rm django python manage.py test --keepdb
Run management scripts
docker compose run django python manage.py --help
Launch the Django shell:
docker compose exec django python manage.py shell
>>> from ami.main.models import SourceImage, Occurrence
>>> SourceImage.objects.all(project__name='myproject')
Install backend dependencies locally for IDE support (Intellisense, etc):
python -m venv venv
source venv/bin/activate
pip install -r requirements/local.txt
Generate OpenAPI schema
docker compose run --rm django python manage.py spectacular --api-version 'api' --format openapi --file ami-openapi-schema.yaml
Generate TypeScript types from OpenAPI schema
docker run --rm -v ${PWD}:/local openapitools/openapi-generator-cli generate -i /local/ami-openapi-schema.yaml -g typescript-axios -o /local/ui/src/api-schema.d.ts
Generate diagram graph of Django models & relationships (Graphviz required)
docker compose run --rm django python manage.py graph_models -a -o models.dot --dot
dot -Tsvg models.dot > models.svg
Project Data Storage
Each project manages its own external data storage where the AMI Platform will index and process images. This is most typically a public or private S3 bucket at a cloud provider that is not AWS. For example, the Swift object storage service at Compute Canada or a university's own storage service.
To test the S3 storage backend locally, Minio is configured to run as part of the docker compose stack.
To configure a project connect to the Minio service, you can use the following config:
Endpoint URL: http://minio:9000
Access key: amistorage
Secret access key: amistorage
Public base URL: http://minio:9000/ami/
Bucket: ami
- Open the Minio web interface at http://localhost:9001 and login with the access key and secret access key.
- Upload some test images to a subfolder in the
ami
bucket (one subfolder per deployment) - Give the bucket or folder anonymous access using the "Anonymous access" button in the Minio web interface.
- Both public and private buckets with presigned URLs should work.
- Add entries to your local
/etc/hosts
file to map theminio
anddjango
hostnames to localhost so the same image URLs can be viewed in your host machine's browser and processed in the backend containers.
127.0.0.1 minio
127.0.0.1 django
The local environment uses the console
email backend. To view emails sent by the platform, check the console output (run the docker compose logs -f django celeryworker
command).
Database
The local environment uses a local PostgreSQL database in a Docker container.
Backup and Restore
docker compose run --rm postgres backup
Reset the database
docker compose run --rm django python manage.py reset_db
Show backups
docker compose run --rm postgres backups
Restore a backup
docker compose run --rm postgres restore <backup_file_name>
Load fixtures with test data
docker compose run --rm django python manage.py migrate