tarilabs / rhoai-rh1-testdrive

Red Hat OpenShift AI Test Drive

General Development Information

Working with this repo

• main branch is the one used for production. That's where the Prod and Test catalog items from demo.redhat.com point to (instructions, materials used,...).
• dev branch is for development. That's where the Dev catalog item points to.
• Branches are made from dev (hot fixes could be made from main if really needed).
• When ready, PRs should be made to dev. Once all features, bug fixes,... are checked in and tested for a new release, another PR will be made from dev to main.
• Branches must be prefixed with /feature (example feature/new-pipeline-instructions), bugfix, or other meaningful info.
• Add your name/handle in the branch name if needed to avoid confusion.
• If your development relates to an Issue or a Feature Request, add its reference in the branch name.
• Try to stash your changes before submitting a PR.

Instructions Development

Requirements

• Podman or Docker

Development

• Add/Modify/Delete content in instructions/content/modules/ROOT.
• Navigation is handled in nav.adoc.
• Content pages are in the pages folder.
• To build the site, from the root of the repo, run ./instructions/utilities/lab-build.
• To serve the site for previewing, from the root of the repo, run instructions/utilities/lab-serve.
• The site will be visible at http://localhost:8443/
• When finished, you can stop serving the site by running from the root of the repo instructions/utilities/lab-stop.

Application Development

Requirements

• Python 3.11
• Nodejs > 18
• An existing instance of Hugging Face TGI with a loaded model available at INFERENCE_SERVER_URL. This application is based on Mistral-TB Prompt format. You will need to modify this format if you are using a different model.

Installation

Run npm install from the main folder.

If you want to install packages manually:

• In the frontend folder, install the node modules with npm install.
• In the backend folder, create a venv and install packages with the provided Pipfile/Pipfile.lock files.
• In the backend folder, create the file .env base on the example .env.example an488962
• ccccccevjcnkhultbvdgrjghjcvgluedrvinjdjfbjch
• d enter the configuration for the Inference server.

Development

From the main folder, launch npm run dev. This will launch both backend and frontend.

• Frontend is accessible at http://localhost:9000
• Backend is accessible at http://localhost:5000, with Swagger API doc at http://localhost:5000/docs