bvandeusenandClaude Opus 4.8
ec66ea5f83
Tier-3 frontend DRY for the ML settings cards, plus the F-D2 clamp bug and the F-D3 card misgrouping. New primitives (components/common + composables): - <SettingToggleRow> — the accent-icon + .fc-section-h label + right-aligned switch row (HeadsCard x3, CropProposersCard). iconColor prop absorbs the on/off dim. - <SettingNumberField> — compact numeric field that CLAMPS to [min,max] on commit. This fixes F-D2: HeadsCard/CropProposersCard previously sent Number(raw) straight to the API, so an out-of-range threshold bounced off the 400 validator (only TranslationCard clamped). density prop for the grid cards. - useSettingSave(patchFn) — the busy + patch + toast + revert-on-failure flow each card hand-rolled (HeadsCard x6 handlers, CropProposersCard, MLBackfillCard, VideoEmbeddingCard). Returns ok/false for the optimistic-switch revert. Adopted in HeadsCard, CropProposersCard, MLBackfillCard (handler only — its plain labelled switch is a different affordance), VideoEmbeddingCard. F-D3: MLThresholdSliders.vue actually rendered a "Video embedding" (frame- sampling) card but sat under "Tagging → Suggestion thresholds". Renamed it VideoEmbeddingCard.vue and moved it to the "GPU agent & embeddings" section. Left deliberately (over-DRY guard): TranslationCard uses an inline error ALERT (not a toast), already clamps its confidence with a NaN fallback, and lives on the ImportStore — a genuinely different save pattern, so forcing it onto useSettingSave would change its UX. Behaviour-preserving refactor; CI has no Vue type-check so this needs a live UI pass (toggles persist + revert on failure, thresholds clamp on blur, video card now under Embeddings). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NsmJSQxnNxGgtM5Yz4GAqi
76 lines
2.8 KiB
Vue
76 lines
2.8 KiB
Vue
<template>
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<MaintenanceTile
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icon="mdi-refresh"
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title="CPU embedding backfill"
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blurb="Whole-image embeddings without a GPU agent — the built-in fallback."
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:open="busy"
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>
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<p class="text-body-2 mb-3">
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Computes the whole-image SigLIP embedding for anything missing one —
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images directly, videos by sampling frames (the same approach as the
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GPU agent). Runs on the ml-worker's CPU, so search, similarity and
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head suggestions work <strong>without</strong> a GPU agent; new imports
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are embedded this way automatically. Detection, cropping and character
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(CCIP) embeddings are GPU-agent-only. Safe to re-run. To re-embed under
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a NEW model, use the GPU agent's "Re-embed library" instead.
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</p>
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<v-switch
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v-model="enabled" color="accent" hide-details density="compact"
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:loading="saving" label="CPU embedding enabled"
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class="mb-1" @update:model-value="onToggle"
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/>
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<p class="fc-muted text-caption mb-3">
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Turn OFF if you run the GPU agent and removed the ml-worker container —
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imports then stop queueing CPU embed work nothing will consume (the
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daily GPU embed backfill covers those images instead).
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</p>
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<v-btn
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color="primary" rounded="pill" :loading="busy" :disabled="!enabled"
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@click="run"
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>
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<v-icon start>mdi-refresh</v-icon> Run backfill now
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</v-btn>
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<span v-if="done" class="ml-3 text-caption">Enqueued.</span>
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<QueueStatusBar queue="ml" queue-label="ML" />
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</MaintenanceTile>
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</template>
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<script setup>
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import { toast } from '../../utils/toast.js'
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import { onMounted, ref } from 'vue'
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import { useMLStore } from '../../stores/ml.js'
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import { useSettingSave } from '../../composables/useSettingSave.js'
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import MaintenanceTile from '../common/MaintenanceTile.vue'
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import QueueStatusBar from './QueueStatusBar.vue'
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const store = useMLStore()
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const { busy: saving, save } = useSettingSave(store.patchSettings)
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const busy = ref(false)
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const done = ref(false)
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const enabled = ref(true)
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onMounted(async () => {
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try {
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await store.loadSettings()
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if (store.settings?.cpu_embed_enabled != null) {
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enabled.value = store.settings.cpu_embed_enabled
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}
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} catch { /* non-fatal */ }
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})
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async function onToggle() {
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const ok = await save({ cpu_embed_enabled: enabled.value }, {
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successMessage: enabled.value
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? 'CPU embedding on — imports queue embeds for the ml-worker'
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: 'CPU embedding off — the GPU embed backfill owns whole-image embeds',
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})
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if (!ok) enabled.value = !enabled.value
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}
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async function run() {
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busy.value = true
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try { await store.triggerBackfill(); done.value = true }
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catch (e) { toast({ text: e.message, type: 'error' }) }
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finally { busy.value = false }
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}
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</script>
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<style scoped>
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</style>
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