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.

ml/tests/test_features.py

@@ -0,0 +1,38 @@
+import math
+
+import pandas as pd
+
+from rarelens_ml.features import RAW_COLUMNS, build
+
+
+def raw(**overrides: list) -> pd.DataFrame:
+    base = {
+        "impact": ["HIGH", "LOW", None],
+        "consequence": ["stop_gained", "synonymous_variant", None],
+        "gnomad_af": [None, "0.12", 0.001],
+        "cadd_phred": ["35", "2.1", "-"],
+        "am_pathogenicity": ["0.98", None, "-"],
+    }
+    base.update(overrides)
+    return pd.DataFrame(base, index=[10, 11, 12])
+
+
+def test_raw_columns_are_the_serving_contract() -> None:
+    assert RAW_COLUMNS == ["impact", "consequence", "gnomad_af", "cadd_phred", "am_pathogenicity"]
+
+
+def test_build_ranks_impact_and_coerces_numbers() -> None:
+    out = build(raw())
+    assert out["impact_rank"].tolist() == [3, 1, 0]
+    assert out["gnomad_af"].tolist() == [0.0, 0.12, 0.001]  # missing AF means absent from gnomAD
+    assert out["cadd_phred"].iloc[0] == 35.0
+    assert math.isnan(out["cadd_phred"].iloc[2])  # VEP writes "-" for missing
+    assert math.isnan(out["am_pathogenicity"].iloc[1])
+
+
+def test_build_keeps_the_input_index() -> None:
+    assert build(raw()).index.tolist() == [10, 11, 12]
+
+
+def test_build_makes_consequence_categorical() -> None:
+    assert isinstance(build(raw())["consequence"].dtype, pd.CategoricalDtype)