b-step62 / ml-assignment

ML Assignment

Please implement a translation inference service that runs on Kubernetes and provides a RESTful API on port 9527.

The translation model is M2M100, and the example can be found in app/translation_example.py.

You should first fork this repository, and then send us the code or the url of your forked repository via email.

Please do not submit any pull requests to this repository.

Delivery

• app/Dockerfile: To generate an application image
• k8s/deployment.yaml: To deploy image to Kubernetes
• Other necessary code

[[Note from author]]

As I have no personal kubernetes environment, I built my solution with docker-compose and translate it to kubernetes definition using Kompose, but haven't verify it if really works or not on k8s. To reproduce original result with docker-compose, please run docker compose up on the top directory.

Input/Output

When you execute this command:

curl --location --request POST 'http://127.0.0.1:9527/translation' \
--header 'Content-Type: application/json' \
--data-raw '{
    "payload": {
        "fromLang": "en",
        "records": [
            {
                "id": "123",
                "text": "Life is like a box of chocolates."
            }
        ],
        "toLang": "ja"
    }
}'

Should return:

{
   "result":[
      {
         "id":"123",
         "text":"人生はチョコレートの箱のようなものだ。"
      }
   ]
}

Bonus points

• Clean code
• Scalable architecture
• Good inference performance
• Efficient CPU/GPU utilization