A Docker-powered service for converting files supported by Libreoffice to PDF.

• Redis server for managing queues
• Docker (install)
• Docker-compose (install)
  • Note: On mac Docker-compose is installed with Docker

Start the service:

./run start

This script will start the service with default configurations.

Default configuration values are as follows:

REDIS_HOST=localhost
REDIS_PORT=6379
SERVICE_HOST=127.0.0.1
SERVICE_PORT=5060

A Python virtual env is needed for some of the development tasks

./run install_venv

Start the service for testing (with a redis server included)

./run start

Check service is up and get general info on supported languages and other important information:

curl localhost:5060/info

Test converting to PDF is working

curl -X POST -F 'file=@./src/test_files/sample-english.pdf' localhost:5060 --output english.pdf

To list all available commands just run ./run, some useful commands:

./run test
./run linter
./run check_format
./run formatter

• Asynchronous OCR
• HTTP server
• Retrieve OCRed PDF
• Queue processor
• Service configuration
• Troubleshooting

1. Upload the file to the service

   curl -X POST -F 'file=@/PATH/TO/PDF/pdf_name.pdf' localhost:5060/upload/[namespace]

The enpoint sends a message to the Redis queue to be processed asynchronously by the worker

2. Retrieve converted PDF

Upon completion of the OCR process, a message is placed in the ocr_results Redis queue. This response is, for now, using specific Uwazi terminology. To check if the process for a specific file has been completed:

queue = RedisSMQ(host=[redis host], port=[redis port], qname='ocr_results', quiet=True)
results_message = queue.receiveMessage().exceptions(False).execute()

# The message.message contains the following information:
# {
#   "namespace": "namespace",
#   "task": "pdf_name.pdf",
#   "success": true,
#   "error_message": "",
#   "file_url": "http://localhost:5050/processed_pdf/[namespace]/[pdf_name]"
#   }


curl -X GET http://localhost:5050/processed_pdf/[namespace]/[pdf_name]

The container HTTP server is coded using Python 3.10 and uses the FastApi web framework.

The endpoints code can be found inside the file ./src/api/app.py.

The container Queue processor is coded using Python 3.10, and it is in charge of communications with the Redis queue.

The code can be found in the file ./src/worker/queue_processor.py and it uses the library RedisSMQ to interact with the Redis queues.