feat(pipeline): VEP database mode, and a pipeline-specific database URL

Makes a real annotation runnable locally without the 25 GB VEP cache, which is what
the demo needs and what a reviewer can reproduce in minutes.

- params.vep_database (VEP_DATABASE=true) queries Ensembl's public database instead of
  a local cache. Slower per variant and fewer fields, so --everything is swapped for the
  flags the loader actually stores. Its cache placeholder is NO_CACHE, not NO_FILE:
  Nextflow rejects two staged inputs sharing a filename.
- PIPELINE_DATABASE_URL is handed to the pipeline when set. The loader runs inside a
  container, where the API's own localhost URL would point at the container itself.
- README: how to run the UI's annotate button locally against host Nextflow + Docker.

Verified end to end on pipeline/tests/data/tiny.vcf: bcftools norm split the multiallelic
record, VEP 113 annotated 4 variants live, the loader wrote them and marked the job
succeeded, and the UI shows them. The deletion came back as 22:42126611 CT>C with exact
VCF alleles, which is the case the audit's ID-tagging fix exists for.

Tests: api 51, loader 16, stub run 3/3; ruff, mypy clean.

api/app/config.py

@@ -23,6 +23,9 @@ class Settings(BaseSettings):
     gcp_project: str | None = None         # required with pubsub_topic or cloudrun_job
     gcp_region: str = "europe-west2"
     pipeline_dir: Path = REPO_ROOT / "pipeline"
+    # Handed to the pipeline when it differs from the API's own: the loader runs inside a
+    # container, where the API's localhost would be the container itself.
+    pipeline_database_url: str | None = None
     nextflow_profile: str = "docker"
     # Local (non-gs://) VCFs must live under this directory.
     local_data_root: Path = Path("/data")