ServingMLFastCelery

Working example for serving a ML model using FastAPI and Celery.

Usage

Install requirements:

pip install -r requirements.txt

Set environment variables:

• MODEL_PATH: Path to pickled machine learning model
• BROKER_URI: Message broker to be used by Celery e.g. RabbitMQ
• BACKEND_URI: Celery backend e.g. Redis

export MODEL_PATH=...
export BROKER_URI=...
export BACKEND_URI=...

Start API:

uvicorn app:app

Start worker node:

celery -A celery_task_app:worker worker -l info