Steps to build websites with the I.R.S module

1. Set Up the Drupal Environment

• Install Drupal using the official drupal:latest Docker image or a standard hosting environment.
• Use the default modules which are enabled when installing Drupal.
• Use composer to add the community contributed module named, irs.

2. Prepare the Required Data Files

Create and make two files available and ensure they’re accessible via Drupal:

• Substitution Graph File (e.g., JSON or CSV): Defines ingredient relationships.
• Metadata File: Includes nutritional info, pricing, allergen tags, and usage feedback.

You can store these in public://, AWS S3, or another cloud bucket, and read them in the module.

3. Enable Modular ML Prediction Engines

Build a pluggable service system for prediction:

• Allow each engine to implement a prediction interface (e.g., IngredientSubstitutionPredictorInterface).
• Drop in different ML models as plugins to:
  • Generate ingredient substitutions
  • Update prices
  • Integrate user feedback (e.g., decrease weight for faulty items like "aluminum foil")

This makes the system extensible and model-agnostic.

4. Incorporate Feedback

• Store feedback to the database using the contributed module Webform.

5. Test and Deploy

• Test the full data pipeline (from file ingestion to prediction display).
• Schedule jobs (e.g., via cron) to periodically ingest updated files or retrain models.