fix: overhaul the platform skeleton, add a serverless deployment track

An end-to-end audit found the repo could not build, test or run as shipped. This
fixes every finding, then adds a Cloud Run track so the demo costs about £1/month
idle instead of ~£150.

CI (red on its first run)
- api: setuptools could not build the package (flat layout with app/ and alembic/)
- web: missing @types/node; `vitest run` exited 1 with no test files
- pipeline: the stub run needed a gitignored VCF, and no process had a stub block
- ruff pinned, mypy configured, DB tests on real Postgres (pgserver locally, service in CI)

ML serving (scores were meaningless)
- the registered model now carries its own feature engineering and returns predict_proba,
  so serving sends raw columns and cannot drift from training
- resolve by registry alias (stages are deprecated in MLflow 3) and record the real
  version; re-scoring upserts instead of failing on the unique constraint
- ClinVar labels parsed from VEP's lowercase terms

Pipeline
- exact ref/alt recovered from a CHROM_POS_REF_ALT VCF ID; loading is idempotent
- job status reaches running/failed/succeeded, so the UI stops polling dead jobs
- DATABASE_URL travels in the environment or a Nextflow secret, never on a command line
- VEP cache and plugins staged as inputs; the gcp profile runs tasks on Google Batch

Deployment
- the API serves /api (matching the ingress); the web app reads its API URL at runtime
- migrations run in an init container under a Postgres advisory lock
- terraform: custom VPC shared with Batch, private Cloud SQL, API enablement, Workload
  Identity bindings, Secret Manager, deletion protection
- serverless track, now the default: Cloud Run services scaling to zero, a Cloud Run job
  for the Nextflow driver, and Neon or Cloud SQL behind one DATABASE_URL secret. GKE and
  Argo remain, behind -var deploy_kubernetes=true. See docs/cloud.md.

Correctness and security
- 409 on duplicate sample names, 422 on bad paging, natural chromosome ordering, wider
  VEP text columns, enum dropped on downgrade, the sample's assembly actually used
- vcf_uri restricted to gs:// objects or files under the data root, blocking option injection
- CORS restricted to configured origins; `make down` no longer deletes volumes

Data
- docs/data.md records the peer-reviewed, openly licensed sources (GIAB HG002, ClinVar,
  gnomAD) with citations and an honest evaluation plan; `make data` fetches a chr22 slice

Verified: api 50 tests, ml 18, loader 16, web 12; ruff, mypy, svelte-check, terraform
validate and both kustomize overlays clean.

infra/terraform/network.tf

@@ -1,4 +1,31 @@
 resource "google_compute_network" "vpc" {
   name                    = "rarelens-vpc"
-  auto_create_subnetworks = true
+  auto_create_subnetworks = false
+  depends_on              = [google_project_service.enabled]
+}
+
+# Shared by GKE and the Google Batch VMs that run pipeline tasks (pipeline/nextflow.config).
+resource "google_compute_subnetwork" "gke" {
+  name                     = "rarelens-gke"
+  region                   = var.region
+  network                  = google_compute_network.vpc.id
+  ip_cidr_range            = "10.10.0.0/20"
+  private_ip_google_access = true
+}
+
+# Private services access, so Cloud SQL gets a private IP inside this VPC. Only needed with it.
+resource "google_compute_global_address" "private_services" {
+  count         = var.deploy_cloud_sql ? 1 : 0
+  name          = "rarelens-private-services"
+  purpose       = "VPC_PEERING"
+  address_type  = "INTERNAL"
+  prefix_length = 16
+  network       = google_compute_network.vpc.id
+}
+
+resource "google_service_networking_connection" "private_services" {
+  count                   = var.deploy_cloud_sql ? 1 : 0
+  network                 = google_compute_network.vpc.id
+  service                 = "servicenetworking.googleapis.com"
+  reserved_peering_ranges = [google_compute_global_address.private_services[0].name]
 }