feat(augaman): deploy v0.1.1 on esh-ml1:8040 (face recognition for Cicada)

Mirror pfi/augaman deploy/compose.yaml as stacks/augaman, with an .env.example and
a README carrying the biometric backup gate. The image is built on esh-ml1 from a
git archive of the release tag, because the box holds no gitea credentials.

Serving on CUDA and visible in nvidia-smi. The gallery backup is not wired yet
(esh-ml1 has no restic), so only public-domain fixtures may be enrolled.
The on-box gpu test fails its batch-vs-single tolerance 3/3; reported to
augaman-dev, who owns the contract.

servers/esh-ml1/README.md

@@ -42,6 +42,13 @@ because TEI cannot serve a Llama classifier. Audit and parity:
 [`stacks/reward-seat/README.md`](../../stacks/reward-seat/README.md). GPU total
 with all three: ~10.4 of 16.4 GB.
 
+**Also here since 2026-09-26: augaman** — `stacks/augaman`, the face-recognition
+service for Cicada (ONNX Runtime CUDA) on `:8040`, image built on this box.
+~0.5 GB VRAM (GPU total with all four: ~11.7 of 16.4 GB). ⚠ It holds **biometric
+data** in the `augaman_gallery` volume, and this CT is outside vzdump: see the
+stack README's backup gate. ⚠ Each augaman release build needs ~10 GB of
+transient disk; prune the old image first (the v0.1.1 build hit 90%).
+
 **Cut-over verified 2026-09-25** through the gateway against fv-ml1's vLLM seats
 just before they were retired: embed cosine median 0.999927 / min 0.999881
 (n=203); rerank top-1 and top-3 agreement 29/30. Two of the 30 lists contained