Load a db with randomly created pizzas in JSON format, then pass a sample pizza to the recommendation service to find similar pizzas using a Weaviate query.
Ro run this project you will need an account with Weaviate, which you can get for free at https://weaviate.io. You will also need a Hugging Face account: https://huggingface.co/.
Use the endpoint and api key from Weaviate, as well as the Hugging Face token to fill in the values in config.py.
Then, run pizza_loader.py to load your vector db with random pizzas. You may run it multiple times to load more pizzas, but you should comment out the schema creation statement at line 28, as it only needs to be executed once.
Now you can run recommendation_service.py, which is a Flask microservice.
python -m flask --app recommendation_service run
Finally, POST a sample pizza in JSON format and you should get three suggestions back, aloong with their certainty scores.