You can help this project by running the OCR worker on your machine. It connects to RabbitMQ, processes OCR tasks, and sends results back.
Create a new folder (example: quinfall-worker) and add a file named docker-compose.yml with this:
services:
ocr_consumer:
image: akjroller1995/quinfall-ocr-consumer:latest
container_name: quinfall_ocr_consumer
restart: unless-stopped
environment:
RABBITMQ_HOST: rabbitmq.therollermethod.com
RABBITMQ_PORT: 5672
RABBITMQ_USER: ocr_client
RABBITMQ_PASS: guest1234
RABBITMQ_INPUT_QUEUE: ocr_tasks
RABBITMQ_OUTPUT_QUEUE: ocr_results
watchtower:
image: containrrr/watchtower
container_name: quinfall_watchtower
restart: unless-stopped
volumes:
- /var/run/docker.sock:/var/run/docker.sock
command: --cleanup --interval 300 quinfall_ocr_consumer
Notes: Watchtower checks every 5 minutes (300s) and automatically updates the worker if a new image is published.
In that folder, run:
docker compose up -d
To check logs:
docker logs -f quinfall_ocr_consumer
To stop:
docker compose down