release: v0.4.1 — code quality fixes and doc updates

Remove unsafe `as any` casts, fix MetricsPage fetch cancellation safety,
delete dead AppBarGpuBadge component, fix typo in data context, move
extractJsonData to module scope, resolve ESLint/Prettier indent conflict,
fix artifacthub-pkg.yml version mismatch and inaccurate description.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/api/IntelGpuDataContext.tsx

@@ -65,6 +65,18 @@ export function useIntelGpuContext(): IntelGpuContextValue {
   return ctx;
 }
 
+// ---------------------------------------------------------------------------
+// Helpers
+// ---------------------------------------------------------------------------
+
+/** Extract raw Kubernetes JSON from Headlamp KubeObject wrappers. */
+const extractJsonData = (items: unknown[]): unknown[] =>
+  items.map(item =>
+    item && typeof item === 'object' && 'jsonData' in item
+      ? (item as { jsonData: unknown }).jsonData
+      : item
+  );
+
 // ---------------------------------------------------------------------------
 // Provider
 // ---------------------------------------------------------------------------
@@ -129,8 +141,8 @@ export function IntelGpuDataProvider({ children }: { children: React.ReactNode }
           try {
             const list = await ApiProxy.request(url);
             if (!cancelled && isKubeList(list)) {
-              const gpuPluinPods = filterIntelGpuPluginPods(list.items);
-              foundPluginPods.push(...gpuPluinPods);
+              const gpuPluginPods = filterIntelGpuPluginPods(list.items);
+              foundPluginPods.push(...gpuPluginPods);
             }
           } catch {
             // Silently ignore — some selectors may not match
@@ -170,13 +182,6 @@ export function IntelGpuDataProvider({ children }: { children: React.ReactNode }
   // type helpers work correctly.
   // ---------------------------------------------------------------------------
 
-  const extractJsonData = (items: unknown[]): unknown[] =>
-    items.map(item =>
-      item && typeof item === 'object' && 'jsonData' in item
-        ? (item as { jsonData: unknown }).jsonData
-        : item
-    );
-
   const gpuNodes = useMemo(() => {
     if (!allNodes) return [];
     return filterIntelGpuNodes(extractJsonData(allNodes as unknown[]));

src/components/AppBarGpuBadge.tsx

@@ -1,46 +0,0 @@
-/**
- * AppBarGpuBadge — compact Intel GPU health indicator in the Headlamp app bar.
- *
- * Shows a status chip in the top navigation bar summarising GPU plugin health.
- * Hides itself when no Intel GPU plugin is detected.
- */
-
-import { StatusLabel } from '@kinvolk/headlamp-plugin/lib/CommonComponents';
-import React from 'react';
-import { useIntelGpuContext } from '../api/IntelGpuDataContext';
-
-export default function AppBarGpuBadge() {
-  const { pluginInstalled, gpuNodes, devicePlugins, loading } = useIntelGpuContext();
-
-  // Hide when loading or no plugin present
-  if (loading || !pluginInstalled) return null;
-
-  const hasUnhealthyPlugin = devicePlugins.some(p => {
-    const desired = p.status?.desiredNumberScheduled ?? 0;
-    const ready = p.status?.numberReady ?? 0;
-    const unavailable = p.status?.numberUnavailable ?? 0;
-    return (desired > 0 && ready < desired) || unavailable > 0;
-  });
-
-  const status = hasUnhealthyPlugin ? 'warning' : 'success';
-  const nodeCount = gpuNodes.length;
-
-  return (
-    <div
-      style={{
-        display: 'flex',
-        alignItems: 'center',
-        gap: '4px',
-        padding: '0 8px',
-        cursor: 'default',
-      }}
-      title={`Intel GPU: ${nodeCount} node${nodeCount !== 1 ? 's' : ''}`}
-    >
-      <StatusLabel status={status}>
-        <span style={{ fontSize: '11px', fontWeight: 600 }}>
-          Intel GPU{nodeCount > 0 ? ` · ${nodeCount}N` : ''}
-        </span>
-      </StatusLabel>
-    </div>
-  );
-}

src/components/MetricsPage.tsx

@@ -194,30 +194,41 @@ export default function MetricsPage() {
   const [metrics, setMetrics] = useState<GpuMetrics | null>(null);
   const [fetchError, setFetchError] = useState<string | null>(null);
   const [fetching, setFetching] = useState(false);
+  const [fetchSeq, setFetchSeq] = useState(0);
 
-  const doFetch = useCallback(async () => {
-    setFetching(true);
-    setFetchError(null);
-    try {
-      const result = await fetchGpuMetrics();
-      setMetrics(result);
-      if (!result) {
-        setFetchError(
-          'Could not reach Prometheus. Ensure kube-prometheus-stack is installed in the monitoring namespace.'
-        );
-      }
-    } catch (e: unknown) {
-      setFetchError(e instanceof Error ? e.message : String(e));
-    } finally {
-      setFetching(false);
-    }
+  const doFetch = useCallback(() => {
+    setFetchSeq(s => s + 1);
   }, []);
 
   useEffect(() => {
-    if (!ctxLoading) {
-      void doFetch();
-    }
-  }, [ctxLoading, doFetch]);
+    if (ctxLoading) return;
+
+    let cancelled = false;
+    setFetching(true);
+    setFetchError(null);
+
+    fetchGpuMetrics()
+      .then(result => {
+        if (cancelled) return;
+        setMetrics(result);
+        if (!result) {
+          setFetchError(
+            'Could not reach Prometheus. Ensure kube-prometheus-stack is installed in the monitoring namespace.'
+          );
+        }
+      })
+      .catch((e: unknown) => {
+        if (cancelled) return;
+        setFetchError(e instanceof Error ? e.message : String(e));
+      })
+      .finally(() => {
+        if (!cancelled) setFetching(false);
+      });
+
+    return () => {
+      cancelled = true;
+    };
+  }, [ctxLoading, fetchSeq]);
 
   if (ctxLoading) {
     return <Loader title="Loading Intel GPU data..." />;

src/components/NodeDetailSection.tsx

@@ -52,11 +52,11 @@ export default function NodeDetailSection({ resource }: NodeDetailSectionProps)
     metadata: { name: string; labels?: Record<string, string> };
   };
 
-  const nodeName = (node as { metadata: { name: string } }).metadata.name;
-  const capacity = getGpuResources((node as any).status?.capacity);
-  const allocatable = getGpuResources((node as any).status?.allocatable);
+  const nodeName = node.metadata.name;
+  const capacity = getGpuResources(node.status?.capacity);
+  const allocatable = getGpuResources(node.status?.allocatable);
 
-  const gpuType = getNodeGpuType(node as any);
+  const gpuType = getNodeGpuType(node);
 
   // Find GPU pods scheduled on this node
   const podsOnNode = loading ? [] : gpuPods.filter(p => p.spec?.nodeName === nodeName);