Files
FabledCurator/frontend/src/components/settings/GpuAgentCard.vue
T
bvandeusen c6f38b0dac feat(tagging): SigLIP concept crops + max-over-bag scoring (#114)
Lift recall on small/local concepts (glasses, cum, stomach-bulge, xray,
lactation) that the whole-image SigLIP vector washes out: the GPU agent now
embeds figure crops with SigLIP too, stored as kind='concept' regions, and the
suggestion rail scores each image as a BAG (whole-image + every concept crop),
taking each head's MAX over the bag. The whole-image vector is always in the
bag, so this can never score lower than before.

Model-agnostic by construction: the server ANNOUNCES the embedding model
(HF name + version) in the lease, so the agent loads whatever the heads were
trained in and stays in lock-step — a model swap is a server setting + a
re-embed migration, never an agent change.

- agent: model-agnostic CropEmbedder (torch/transformers get_image_features,
  fp16 on CUDA, inference-locked); worker branches on job.task — 'ccip' emits
  figure(CCIP)+concept(SigLIP) in one pass, 'siglip' emits concept-only so the
  back-catalogue backfill never churns figure/CCIP regions; torch cu124 +
  transformers in the image.
- server: lease announces embed_model_name/embed_version; score_image is
  max-over-bag (version-filtered region embeddings); enqueue_gpu_backfill
  'siglip' gates on a missing concept region (drains the back-catalogue,
  retries failures, no double-enqueue); daily siglip-backfill beat; UI button;
  /api/ccip/overview reports images_with_concept_siglip.
- v1 scope: suggestion rail only — auto-apply stays whole-image (conservative;
  heads' thresholds were calibrated on whole-image). Bulk-apply bag = follow-up.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
2026-06-30 08:17:47 -04:00

271 lines
9.7 KiB
Vue

<template>
<MaintenanceTile
icon="mdi-expansion-card"
title="GPU agent (CCIP + crops)"
blurb="Connect a desktop-GPU agent to embed characters (CCIP) and crops. It pulls work over HTTP — your database and Redis stay private."
:open="true"
>
<p class="fc-muted text-body-2 mb-3">
The agent is a container you run on the machine with the GPU. It
authenticates with the token below, leases jobs from this server, computes
on the GPU, and posts results back all over HTTP. Start it when you want
a burst; stop it to reclaim the card.
</p>
<!-- Token -->
<div class="fc-section-h mb-1">Agent token</div>
<div v-if="loading" class="fc-muted text-body-2">Loading</div>
<template v-else>
<div v-if="tokenValue" class="fc-token">
<code class="fc-token__val">{{ masked ? maskedToken : tokenValue }}</code>
<v-btn
size="x-small" variant="text" :icon="masked ? 'mdi-eye' : 'mdi-eye-off'"
:title="masked ? 'Reveal' : 'Hide'" @click="masked = !masked"
/>
<v-btn
size="x-small" variant="text" icon="mdi-content-copy"
title="Copy token" @click="onCopy"
/>
<v-btn
size="small" variant="text" color="accent" class="ml-auto"
prepend-icon="mdi-refresh" :loading="rotating" @click="onRotate"
>Rotate</v-btn>
</div>
<div v-else>
<v-btn
color="accent" variant="flat" rounded="pill" size="small"
prepend-icon="mdi-key-plus" :loading="rotating" @click="onRotate"
>Generate token</v-btn>
</div>
<p class="fc-muted text-caption mt-2 mb-0">
Point the agent at <code>{{ baseUrl }}</code> with this token. Rotating
invalidates the old token update the agent after you rotate.
</p>
</template>
<!-- Queue -->
<div class="fc-section-h mt-5 mb-2">Work queue</div>
<div class="fc-queue">
<div class="fc-q"><div class="fc-q__n">{{ queue.pending }}</div><div class="fc-q__l">pending</div></div>
<div class="fc-q"><div class="fc-q__n">{{ queue.leased }}</div><div class="fc-q__l">in flight</div></div>
<div class="fc-q"><div class="fc-q__n fc-good">{{ queue.done }}</div><div class="fc-q__l">done</div></div>
<div class="fc-q"><div class="fc-q__n" :class="queue.error ? 'fc-weak' : ''">{{ queue.error }}</div><div class="fc-q__l">errored</div></div>
</div>
<v-btn
class="mt-4" color="accent" variant="tonal" rounded="pill" size="small"
prepend-icon="mdi-account-box-multiple" :loading="backfilling" @click="onBackfill"
>Queue character embedding (CCIP)</v-btn>
<p class="fc-muted text-caption mt-2 mb-0">
Enqueues every image that doesn't have a CCIP embedding yet. Nothing
processes until the agent is running.
</p>
<v-btn
class="mt-3" color="accent" variant="tonal" rounded="pill" size="small"
prepend-icon="mdi-crop" :loading="backfillingSiglip" @click="onBackfillSiglip"
>Queue concept crops (SigLIP)</v-btn>
<p class="fc-muted text-caption mt-2 mb-0">
Enqueues every image that doesn't have concept-crop embeddings yet the
localized vectors that help small/local tags (glasses, etc.) surface. New
images get these automatically; this catches the back-catalogue.
</p>
<!-- Match strictness -->
<div class="fc-section-h mt-5 mb-1">Character-match strictness</div>
<div v-if="ml.settings" class="d-flex align-center" style="gap:12px">
<v-slider
v-model="threshold" :min="0.70" :max="0.95" :step="0.01"
color="accent" hide-details density="compact" class="flex-grow-1"
:loading="savingThreshold" @end="onSaveThreshold"
/>
<span class="fc-q__n" style="font-size:16px">{{ threshold.toFixed(2) }}</span>
</div>
<p class="fc-muted text-caption mt-1 mb-0">
How close a figure must be (CCIP cosine) to suggest a character. Higher =
stricter fewer but more confident matches. 0.85 recommended; below ~0.80
a heavily-tagged character starts matching everything.
</p>
<!-- Auto-apply -->
<div v-if="ml.settings" class="d-flex align-center mt-5" style="gap:12px">
<v-switch
v-model="autoApply" color="accent" hide-details density="compact"
:loading="savingAuto" label="Auto-apply confident matches"
@update:model-value="onSaveAuto"
/>
<v-text-field
v-model.number="autoThreshold" type="number" min="0.80" max="0.99"
step="0.01" density="compact" hide-details variant="outlined"
style="max-width:96px" :disabled="!autoApply" label="at"
@change="onSaveAuto"
/>
</div>
<p class="fc-muted text-caption mt-1 mb-0">
When on, a very-confident character match tags the image on its own (daily,
reversible) so identity tags keep flowing without review. Stricter than
the suggest cut; 0.92 recommended.
</p>
</MaintenanceTile>
</template>
<script setup>
import { toast } from '../../utils/toast.js'
import { computed, onMounted, onUnmounted, ref } from 'vue'
import MaintenanceTile from '../common/MaintenanceTile.vue'
import { useGpuStore } from '../../stores/gpu.js'
import { useMLStore } from '../../stores/ml.js'
import { copyText } from '../../utils/clipboard.js'
const store = useGpuStore()
const ml = useMLStore()
const loading = ref(true)
const tokenValue = ref(null)
const masked = ref(true)
const rotating = ref(false)
const backfilling = ref(false)
const backfillingSiglip = ref(false)
const threshold = ref(0.85)
const savingThreshold = ref(false)
const autoApply = ref(true)
const autoThreshold = ref(0.92)
const savingAuto = ref(false)
const queue = ref({ pending: 0, leased: 0, done: 0, error: 0 })
let pollTimer = null
const baseUrl = computed(() => window.location.origin)
const maskedToken = computed(() => {
const t = tokenValue.value || ''
return t.length > 8 ? `${t.slice(0, 4)}••••••••${t.slice(-4)}` : '••••••••'
})
onMounted(async () => {
try {
tokenValue.value = (await store.token()).token
} catch { /* non-fatal */ } finally {
loading.value = false
}
await refreshQueue()
pollTimer = setInterval(() => { if (!document.hidden) refreshQueue() }, 5000)
try {
await ml.loadSettings()
if (ml.settings?.ccip_match_threshold != null) {
threshold.value = ml.settings.ccip_match_threshold
}
if (ml.settings?.ccip_auto_apply_enabled != null) {
autoApply.value = ml.settings.ccip_auto_apply_enabled
autoThreshold.value = ml.settings.ccip_auto_apply_threshold
}
} catch { /* non-fatal */ }
})
async function onSaveAuto() {
savingAuto.value = true
try {
await ml.patchSettings({
ccip_auto_apply_enabled: autoApply.value,
ccip_auto_apply_threshold: autoThreshold.value,
})
toast({ text: 'Auto-apply settings saved', type: 'success' })
} catch (e) {
toast({ text: `Could not save: ${e.message}`, type: 'error' })
} finally {
savingAuto.value = false
}
}
onUnmounted(() => { if (pollTimer) clearInterval(pollTimer) })
async function onSaveThreshold() {
savingThreshold.value = true
try {
await ml.patchSettings({ ccip_match_threshold: threshold.value })
toast({ text: `Match strictness set to ${threshold.value.toFixed(2)}`, type: 'success' })
} catch (e) {
toast({ text: `Could not save: ${e.message}`, type: 'error' })
} finally {
savingThreshold.value = false
}
}
async function refreshQueue() {
try { queue.value = await store.status() } catch { /* non-fatal */ }
}
async function onRotate() {
rotating.value = true
try {
tokenValue.value = (await store.rotateToken()).token
masked.value = false
toast({ text: 'New agent token generated — update your agent', type: 'success' })
} catch (e) {
toast({ text: `Could not rotate token: ${e.message}`, type: 'error' })
} finally {
rotating.value = false
}
}
async function onCopy() {
try {
await copyText(tokenValue.value || '') // resolves on success, throws on fail
toast({ text: 'Token copied', type: 'success' })
} catch {
toast({ text: 'Copy failed — select and copy manually', type: 'warning' })
}
}
async function onBackfill() {
backfilling.value = true
try {
await store.backfill('ccip')
toast({ text: 'Queued CCIP embedding — run the agent to process it', type: 'success' })
await refreshQueue()
} catch (e) {
toast({ text: `Could not queue backfill: ${e.message}`, type: 'error' })
} finally {
backfilling.value = false
}
}
async function onBackfillSiglip() {
backfillingSiglip.value = true
try {
await store.backfill('siglip')
toast({ text: 'Queued concept crops — run the agent to process them', type: 'success' })
await refreshQueue()
} catch (e) {
toast({ text: `Could not queue backfill: ${e.message}`, type: 'error' })
} finally {
backfillingSiglip.value = false
}
}
</script>
<style scoped>
.fc-muted { color: rgb(var(--v-theme-on-surface-variant)); }
.fc-section-h {
font-size: 13px; font-weight: 700; letter-spacing: 0.03em;
text-transform: uppercase; color: rgb(var(--v-theme-on-surface));
}
.fc-token {
display: flex; align-items: center; gap: 4px;
background: rgb(var(--v-theme-surface-light)); border-radius: 6px;
padding: 4px 6px 4px 10px;
}
.fc-token__val {
font-family: 'JetBrains Mono', monospace; font-size: 13px;
overflow: hidden; text-overflow: ellipsis; white-space: nowrap;
}
.fc-queue { display: flex; gap: 24px; }
.fc-q__n {
font-size: 20px; font-weight: 700; line-height: 1.1;
font-family: 'JetBrains Mono', monospace;
}
.fc-q__l {
font-size: 11px; text-transform: uppercase; letter-spacing: 0.04em;
color: rgb(var(--v-theme-on-surface-variant));
}
.fc-good { color: rgb(var(--v-theme-success)); }
.fc-weak { color: rgb(var(--v-theme-error)); }
</style>