Sunbird NLLB Translate Inference Server

A Sunbird NLLB Translate Inference Server running on the RunPod Endpoint API worker. See the notebook for the nllb translation here and for model training here.

Some of the steps below are optional as you can just build and push the nllb translate image to docker hub by running the commands below.

chmod u+x bin/*
./bin/build
./bin/push

The image repository will be used to build the Runpod Endpoint for the Nllb Translate Inference Server.

Refer to the Runpod documentation on how to get started with building serverless runpod enpoint api worker.

Used the Runpod Worker Template for the stepup and workflow actions.

📖 | Getting Started

1. Clone this repository.
2. (Optional) Add DockerHub credentials to GitHub Secrets.
3. Add your code to the src directory.
4. Update the handler.py file to load models and process requests.
5. Add any dependencies to the requirements.txt file.
6. Add any other build time scripts to thebuilder directory, for example, downloading models.
7. Update the Dockerfile to include any additional dependencies.

⚙️ | CI/CD (GitHub Actions)

As a reference this repository provides example CI/CD workflows to help you test your worker and build a docker image. The three main workflows are:

1. CI-test_handler.yml - Tests the handler using the input provided by the --test_input argument when calling the file containing your handler.

Test Handler

This workflow will validate that your handler works as expected. You may need to add some dependency installations to the CI-test_handler.yml file to ensure your handler can be tested.

The action expects the following arguments to be available:

• vars.RUNNER_24GB | The endpoint ID on RunPod for a 24GB runner.
• secrets.RUNPOD_API_KEY | Your RunPod API key.
• secrets.GH_PAT | Your GitHub Personal Access Token.
• vars.GH_ORG | The GitHub organization that owns the repository, this is where the runner will be added to.

Test End-to-End

This repository is setup to automatically build and push a docker image to the GitHub Container Registry. You will need to add the following to the GitHub Secrets for this repository to enable this functionality:

• DOCKERHUB_USERNAME | Your DockerHub username for logging in.
• DOCKERHUB_TOKEN | Your DockerHub token for logging in.

Additionally, the following need to be added as GitHub actions variables:

• DOCKERHUB_REPO | The name of the repository you want to push to.
• DOCKERHUB_IMG | The name of the image you want to push to.

The CD-docker_dev.yml file will build the image and push it to the dev tag, while the CD-docker_release.yml file will build the image on releases and tag it with the release version.

The CI-test_worker.yml file will test the worker using the input provided by the --test_input argument when calling the file containing your handler. Be sure to update this workflow to install any dependencies you need to run your tests.

Example Input

{
    "input": {
        "source_language": "lug",
        "target_language": "eng",
        "text": "Kifunzibwa n’ekigambo kimu kyokka - muntu.",
    }
}

💡 | Best Practices

System dependency installation, model caching, and other shell tasks should be added to the builder/setup.sh this will allow you to easily setup your Dockerfile as well as run CI/CD tasks.

Models should be part of your docker image, this can be accomplished by either copying them into the image or downloading them during the build process.

If using the input validation utility from the runpod python package, create a schemas python file where you can define the schemas, then import that file into your handler.py file.

🔗 | Links

🐳 Docker Container