Here is an Angular application that helps risk/compliance teams
monitor a model, investigate predictions, and walk through a lightweight compliance checklist.
This is frontend-only; I'm consuming a mocked REST API (provided in data.json).
Here's a slice of a Responsible AI oversight UI for a binary classification model ("CreditRisk–v3"). Users need to:
- See model health & drift at a glance.
- Search & inspect predictions, including explanations.
- Review audit events.
- Complete a compliance checklist and export a summary.
- Card(s) with: model name, version, owner, last deployment, total predictions (24h), error rate (24h),
and drift indicator. Data from
/api/models/:idand/api/metrics/:modelId. - A small sparkline or simple trend chips for latency or accuracy (client-side, from recent metrics).
- A searchable, paginated table from
/api/predictions?modelId=...&q=&page=&limit=. - Columns:
id,timestamp,inputSummary(e.g., age/income),score,decision(Approve/Deny),latencyMs. - Row click opens a details drawer/page showing:
- Full
inputFeatures. explanations(top-k features with contribution).- A compact fairness section showing
sensitiveAttributesand a disclaimer.
- Full
- Stream-like list from
/api/audit?modelId=...&type=&page=with filters bytype(DEPLOY, PREDICT, POLICY, ERROR). - Each item shows timestamp, actor, type, and message.
- Render checklist steps from
/api/checklists/:id. - Let users toggle items complete/incomplete and add a short note per item (local state is fine).
- “Export Summary” → generate a downloadable JSON or plain text summary of current completion.
- ETag-style caching (store last fetched and show "stale" badge).
- A11y polish: focus management when opening details; labelled inputs; visible focus states.
- Error states and retry with exponential backoff for the Predictions list.
- Theming via SCSS variables (light/dark toggle).
- Route structure:
/overview,/predictions,/audit,/compliance.
- Angular (v15+), TypeScript.
- SCSS (SASS) for styling.
- REST-only APIs.
- No backend code.
json-serverto servedata.jsononhttp://localhost:4000, or
Base URL (recommended): http://localhost:4000/api