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OpenShift AI Unleashed: Transforming Claims Processing for Maximum Efficiency!

Introduction

This repository contains the code, instructions, resources and materials associated with the Lab called OpenShift AI Unleashed: Transforming Claims Processing for Maximum Efficiency!.

To consult the static version of the instructions, please use this URL

If you want to participate in the creation and update of this content, please consult the sections below.

Display Development-centric information

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.

How to update the Instructions

Useful link: https://redhat-scholars.github.io/build-course/rhs-build-course/develop.html

Requirements

  • Podman or Docker

Development

  • Add/Modify/Delete content in 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 ./content/utilities/lab-build.
  • To serve the site for previewing, from the root of the repo, run ./content/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 ./content/utilities/lab-stop.

How to update the Application

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 and enter the configuration for the Inference server.

Development

From the main folder, launch npm run dev or ./start-dev.sh. 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
#!/bin/bash

# Script to restart all showroom pods - You must be logged in as a cluster admin to run this script

# Get all namespaces
namespaces=$(oc get namespaces -o jsonpath='{.items[*].metadata.name}' \
    | tr ' ' '\n' \
    | grep '^showroom')

# Stop all the pods
for namespace in $namespaces; do
    # Check if the deployment "showroom" exists in the namespace
    if oc -n $namespace get deployment showroom &> /dev/null; then
        # If it exists, restart the rollout
        # oc -n $namespace rollout restart deployment/showroom
        oc -n $namespace scale deploy showroom --replicas=0
    fi
done


# wait for them all to fully stop
# start all the pods
for namespace in $namespaces; do
    # Check if the deployment "showroom" exists in the namespace
    if oc -n $namespace get deployment showroom &> /dev/null; then
        # If it exists, restart the rollout
        # oc -n $namespace rollout restart deployment/showroom
        oc -n $namespace scale deploy showroom --replicas=1
    fi
done

How to graduate code from dev to main

  • From dev, create a new branch, like feature/prepare-for-main-merge.
  • Modify the following files to make their relevant content point to main:
    • bootstrap/applicationset/applicationset-bootstrap.yaml
    • content/antora.yml
    • content/modules/ROOT/pages/05-03-web-app-deploy-application.adoc
  • Make a pull request from this branch to main, review and merge
Links for Summit event environment assignment

Languages

  • Python 30.4%
  • Jupyter Notebook 25.9%
  • TypeScript 18.2%
  • Shell 17.2%
  • JavaScript 5.3%
  • CSS 1.4%
  • Other 1.6%