bvandeusen
485387ff0b
Heads + CCIP are the tag source and head auto-apply is the earned propagation.
The Camie tagger ran only to feed the allowlist bulk-apply (its ImagePrediction
rows had no other consumer), and the allowlist was a SECOND, un-earned auto-apply
path firing in parallel with heads on every accept — exactly the un-earned spray
the v2 pivot replaced. Retire both.
Behavior change: accepting a suggestion now applies the tag to THAT image only
(source='ml_accepted', a head-training positive) — it no longer allowlists +
fans the tag across the library via Camie. Propagation is heads' earned
auto-apply. (Loses instant cold-start propagation for booru-vocab tags; that was
un-earned and bypassed the precision gate.)
- tag_and_embed is now EMBED-ONLY (no Camie load/infer, no ImagePrediction
writes); backfill enqueues it for images with no embedding.
- Removed: services/ml/tagger.py, apply_allowlist_tags + helpers + daily beat +
every enqueue caller (accept/alias/merge/per-image), api/allowlist.py +
blueprint, ImagePrediction + TagAllowlist models/tables (migration 0067),
AllowlistTable.vue + allowlist store, the accept coverage-projection payload.
- AllowlistService gutted to accept/dismiss/undismiss/reject (the rejection store
the rail still needs); accept returns nothing, API returns {accepted, tag_id}.
- tag merge no longer repoints/triggers the allowlist; _keep_as_alias now keys on
ML-applied image_tag sources (incl. head_auto) instead of the allowlist.
- UI: MLBackfillCard relabelled to embedding-only; accept toast simplified;
MaintenancePanel drops the allowlist tile.
Left for a follow-up hygiene pass (now-inert, harmless): the dead settings
columns (tagger_store_floor, tagger_model_version, suggestion_threshold_*,
video_min_tag_frames), image_record.tagger_model_version, MLThresholdSliders
trim, and the Camie model download in download_models.py.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
37 lines
1.2 KiB
Vue
37 lines
1.2 KiB
Vue
<template>
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<MaintenanceTile
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icon="mdi-refresh"
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title="ML backfill"
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blurb="Compute SigLIP embeddings on images missing them."
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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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Compute the SigLIP embedding for any image that doesn't have one yet
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(CPU). Safe to re-run. To re-embed under a NEW model, use the GPU
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agent's "Re-embed library" instead.
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</p>
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<v-btn color="primary" rounded="pill" :loading="busy" @click="run">
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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 { ref } from 'vue'
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import { useMLStore } from '../../stores/ml.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 = ref(false)
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const done = ref(false)
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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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