feat(ml): default to SigLIP 2 (new installs) + model dropdown, no free-text (#1203)

- Migration 0069: new installs default to SigLIP 2 (so400m, 512px, 1152-d drop-in)
  — UPDATE applies ONLY where no image is embedded yet (fresh install), so an
  existing library is NOT silently invalidated; it switches deliberately via the
  dropdown → Re-embed → Retrain. Column server_defaults moved to SigLIP 2.
- GET /api/ml/embedder-models: server-authoritative supported list (SigLIP 2 512
  recommended / 384 faster / SigLIP 1 384 original) so the UI never free-types.
- GpuAgentCard: the two name/version text fields → a single model dropdown;
  Save sets name+version from the picked option (the current model is always
  selectable even if off-list).
- embedder.py DEFAULT_MODEL_NAME unchanged (stays the baked local-dir SigLIP 1)
  to avoid a local-dir/weights mismatch; SigLIP 2 loads by HF name, cached on the
  ml-worker's persistent HF_HOME.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa

frontend/src/components/settings/GpuAgentCard.vue

@@ -117,15 +117,12 @@
       the suggest cut; 0.92 recommended.
     </p>
 
-    <!-- Embedding model (advanced) -->
-    <div v-if="ml.settings" class="fc-section-h mt-5 mb-1">Embedding model (advanced)</div>
+    <!-- Embedding model -->
+    <div v-if="ml.settings" class="fc-section-h mt-5 mb-1">Embedding model</div>
     <div v-if="ml.settings">
-      <v-text-field
-        v-model="modelName" label="HF model name" density="compact" hide-details
-        variant="outlined" class="mb-2"
-      />
-      <v-text-field
-        v-model="modelVersion" label="Version stamp" density="compact" hide-details
+      <v-select
+        v-model="selectedModel" :items="modelItems" item-title="label"
+        item-value="name" label="Model" density="compact" hide-details
         variant="outlined"
       />
       <div class="d-flex mt-3" style="gap:8px">
@@ -139,12 +136,11 @@
         >Re-embed library (GPU)</v-btn>
       </div>
       <p class="fc-muted text-caption mt-2 mb-0">
-        Changing the model means a DIFFERENT embedding space. After saving a new
-        model + version, run <b>Re-embed library</b> (the GPU agent re-embeds
-        whole images + concept crops), then <b>Retrain heads</b>. Suggestions
-        degrade until both finish. SigLIP 2 (<code>google/siglip2-so400m-patch16-512</code>,
-        version <code>siglip2-so400m-patch16-512</code>) is a 1152-d drop-in at
-        512px — no schema change.
+        Switching the model is a DIFFERENT embedding space. After <b>Save model</b>,
+        run <b>Re-embed library</b> (the GPU agent re-embeds whole images + concept
+        crops), then <b>Retrain heads</b> — suggestions degrade until both finish.
+        SigLIP 2 (512px) is a 1152-d drop-in over SigLIP 1; new installs default to
+        it. Your existing library stays on its current model until you re-embed.
       </p>
     </div>
   </MaintenanceTile>
@@ -173,8 +169,8 @@ const savingThreshold = ref(false)
 const autoApply = ref(true)
 const autoThreshold = ref(0.92)
 const savingAuto = ref(false)
-const modelName = ref('')
-const modelVersion = ref('')
+const modelItems = ref([])
+const selectedModel = ref(null)
 const savingModel = ref(false)
 const reembedding = ref(false)
 const queue = ref({ pending: 0, leased: 0, done: 0, error: 0 })
@@ -204,18 +200,26 @@ onMounted(async () => {
       autoThreshold.value = ml.settings.ccip_auto_apply_threshold
     }
     if (ml.settings?.embedder_model_name != null) {
-      modelName.value = ml.settings.embedder_model_name
-      modelVersion.value = ml.settings.embedder_model_version
+      const items = await ml.embedderModels()
+      // Make sure the current model is selectable even if it's not in the list.
+      const cur = ml.settings.embedder_model_name
+      if (!items.some((m) => m.name === cur)) {
+        items.push({ name: cur, version: ml.settings.embedder_model_version, label: `${cur} (current)` })
+      }
+      modelItems.value = items
+      selectedModel.value = cur
     }
   } catch { /* non-fatal */ }
 })
 
 async function onSaveModel() {
+  const opt = modelItems.value.find((m) => m.name === selectedModel.value)
+  if (!opt) return
   savingModel.value = true
   try {
     await ml.patchSettings({
-      embedder_model_name: modelName.value.trim(),
-      embedder_model_version: modelVersion.value.trim(),
+      embedder_model_name: opt.name,
+      embedder_model_version: opt.version,
     })
     toast({ text: 'Embedding model saved — now Re-embed library, then Retrain heads', type: 'success' })
   } catch (e) {