Phase 11: Embedding versioning — model-proof vector layer

- IndexRegistry: tracks all vector indexes with model metadata
  (model_name, model_version, dimensions, build stats)
- Index metadata persisted as JSON in vectors/meta/
- Rebuilt on startup for crash recovery
- GET /vectors/indexes — list all indexes (filter by source/model)
- GET /vectors/indexes/{name} — get index metadata
- Background jobs auto-register metadata on completion
- Multi-version support: same data, different models, coexist
- Per ADR-014: enables incremental re-embed on model upgrade

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

crates/gateway/src/main.rs

@@ -57,10 +57,15 @@ async fn main() {
             store: store.clone(),
             registry: registry.clone(),
         }))
-        .nest("/vectors", vectord::service::router(vectord::service::VectorState {
-            store: store.clone(),
-            ai_client: ai_client.clone(),
-            job_tracker: vectord::jobs::JobTracker::new(),
+        .nest("/vectors", vectord::service::router({
+            let index_reg = vectord::index_registry::IndexRegistry::new(store.clone());
+            let _ = index_reg.rebuild().await;
+            vectord::service::VectorState {
+                store: store.clone(),
+                ai_client: ai_client.clone(),
+                job_tracker: vectord::jobs::JobTracker::new(),
+                index_registry: index_reg,
+            }
         }))
         .nest("/workspaces", queryd::workspace_service::router(workspace_mgr))
         .nest("/journal", journald::service::router(journal));