mirror of https://github.com/doccano/doccano.git
pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
1.5 KiB
1.5 KiB
Running Doccano with Docker
This guide explains how to run doccano using Docker and Docker Compose, including the steps needed to ensure export functionality.
1. Clone the Repository
git clone https://github.com/doccano/doccano.git
cd doccano
2. Build and Start the Containers
docker compose -f docker/docker-compose.yml up --build
This will start:
- The Django backend
- The frontend UI
- The Celery worker (required for export)
- Redis (for task queue)
3. Access the Web UI
Open http://localhost:8000 in your browser.
4. Create a Superuser
In a new terminal, run:
docker compose -f docker/docker-compose.yml exec backend python manage.py createsuperuser
5. Use Doccano
- Log in with your superuser credentials.
- Create a project, import data, annotate, and export.
6. Stopping Doccano
To stop all services:
docker compose -f docker/docker-compose.yml down
Troubleshooting
- Export not working?
The Celery worker must be running (it is included in the default Docker Compose setup).
If you see no exported file, check the logs of theworker
service:docker compose -f docker/docker-compose.yml logs worker
- Persistent data:
By default, the database is stored in a Docker volume for persistence between runs.