AiPowerHouse UI

A polished UI shell for orchestrating multi-model AI workflows. The interface highlights routing playbooks, governance controls, and a curated roster of leading AI platforms.

Highlights

• Search the model roster instantly by provider name.
• Cycle a capability filter to focus on model specialties.
• View live result counts and an empty-state hint when no model matches.

Getting started

Open index.html in a browser, or use a simple web server:

python3 -m http.server 5173

Validation

Run the standard checks before committing changes:

npm install
npm run format
npm run lint
npm run typecheck
npm run test

ML CI/CD/CT workflow

This repository now includes .github/workflows/ml-cicd.yml, which defines a GitHub Actions pipeline for ML operations with:

• data validation gates before training,
• reproducible training metadata + MLflow logging,
• drift detection checks that can fail builds,
• Kubeflow pipeline compilation/submission, and
• automated MLflow model-registry promotion on main.

Expected project entrypoints for this workflow live under ml/:

• ml/data_validation/run_validation.py
• ml/training/train.py
• ml/monitoring/drift_check.py
• ml/pipelines/training_pipeline.py
• ml/pipelines/submit_pipeline_run.py