# ServingMLFastCelery

**Repository Path**: quminzi/ServingMLFastCelery

## Basic Information

- **Project Name**: ServingMLFastCelery
- **Description**: FastAPI + Celery for model deploy.

https://towardsdatascience.com/deploying-ml-models-in-production-with-fastapi-and-celery-7063e539a5db
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-07-08
- **Last Updated**: 2023-04-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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

## Usage

**Install requirements:**
```bash
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
```bash
export MODEL_PATH=...
export BROKER_URI=...
export BACKEND_URI=...
```

**Start API:**
```bash
uvicorn app:app
```

**Start worker node:**
```bash
celery -A celery_task_app:worker worker -l info
```