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4 changes: 4 additions & 0 deletions .github/workflows/ci.yml
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on:
# Triggers on pushes and on pull requests
push:
paths-ignore:
- 'demos/**'
pull_request:
paths-ignore:
- 'demos/**'

# Allows you to run this workflow manually from the Actions tab
workflow_dispatch:
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155 changes: 155 additions & 0 deletions demos/app_runner/.gitignore
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# job dir
jobs/

# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# C extensions
*.so

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Translations
*.mo
*.pot

# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal

# Flask stuff:
instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
.pybuilder/
target/

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version

# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock

# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock

# PEP 582; used by e.g. github.com/David-OConnor/pyflow
__pypackages__/

# Celery stuff
celerybeat-schedule
celerybeat.pid

# SageMath parsed files
*.sage.py

# Environments
.env
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venv/
ENV/
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# Spyder project settings
.spyderproject
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# Rope project settings
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# mkdocs documentation
/site

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# Pyre type checker
.pyre/

# pytype static type analyzer
.pytype/

# Cython debug symbols
cython_debug/

# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
51 changes: 51 additions & 0 deletions demos/app_runner/README.md
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# DEMO: MONAI Deploy App SDK App Runner Integration

This demo shows how an application integrates with the MONAI Deploy Informatics Gateway (MIG) by subscribing to events emitted by MIG and launches the configured MONAI Deploy Application Package (MAP).


![Demo-AppRunner](./demo-apprunner.png)

## Requirements

- MONAI Deploy Informatics Gateway 0.1.1+
- MONAI Deploy App SDK 0.2.1+
- A MAP from the [examples](https://github.com/Project-MONAI/monai-deploy-app-sdk/tree/main/examples/apps/) or BYO MAP.
- RabbitMQ configured and running
- MinIO configured and running
- Python 3.7+


## Running the demo

1. Install requirements specified above
2. Configure an AET with one or more workflows. For example, the following command would trigger the `dcm-to-img:latest` MAP.
```
mig-cli aet add -a DCM2PNG -w dcm-to-img:latest -v
```
3. Install python dependencies specified in [requirements.txt](./requirements.txt)
4. Edit `config.json` and change:
1. `endpoint`/`host`, `username`, and `password` for both storage and messaging services
2. `bucket` where payloads are stored
5. python app.py

**Notes**: For MONAI Deploy App SDK 0.2.1, set `ignore_json` to `false` in the `config.json` file so DICOM JSON files are not downloaded.

## Job Directory Structure

Both retrieved input dataset and MAP generated output are stored under the `jobs/` directory which is configurable in the
`config.json` file under `working_dir`.

A subdirectory is created for each request received using the `correlation_id` specified in the payload.
Given that one or more workflows can be specified in the payload, output generated from each MAP is stored under `jobs/{correlation_id}/output/{map_name}`.

Sample output of `jobs` directory:
```
└── db61c4fc-b84e-4255-b40a-60254f93ca6f (correlation_id of the request)
├── input
└── output
└── dcm-to-img-latest (name of the workflow/MAP)
```

## Other Ideas

💡 Instead of calling App Runner, integrate with [MIS](https://github.com/Project-MONAI/monai-deploy-app-server)
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