Details

• The backend was built with the Quart framework
• Quart is an asyncio reimplementation of Flask
• All HTTP requests are handled in app.py in the root folder
• Azure Storage API calls are handled in the `azure_storage_api/azure_Storage_api.py
• Inference results from model endpoint are directly handled in model_inference/inference.py

When you are developping, you can run the program while in the devcontainer by using this command:

hypercorn -b :8080 app:app

If you want to run the program as a Docker container (e.g., for production), use:

docker build -t nachet-backend .
docker run -p 8080:8080 -v $(pwd):/app nachet-backend

To test the program, use this command:

python -m unittest discover -s tests

Start by making a copy of .env.template and renaming it .env. For the backend to function, you will need to add the missing values:

• NACHET_AZURE_STORAGE_CONNECTION_STRING: Connection string to access external storage (Azure Blob Storage).
• NACHET_MODEL_ENDPOINT_REST_URL: Endpoint to communicate with deployed model for inferencing.
• NACHET_MODEL_ENDPOINT_ACCESS_KEY: Key used when consuming online endpoint.
• NACHET_DATA: Url to access nachet-data repository
• NACHET_HEALTH_MESSAGE: Health check message for the server.

If you need help deploying Nachet for your own needs, please contact us at [email protected].