feat(llm): add nomic-embed-text-v1.5-Q4_K_M to astro-orbiter router

OpenViking Phase 1b (t_34b96e83) — Ryan-approved implementation.

Changes:
- roles/llm-inference-multimodel/templates/llama-server-router-preset.ini.j2:
  Add [nomic-embed-text-v1.5] section with embedding=true, n-gpu-layers=99,
  ctx-size=8192, load-on-startup=true, sleep-idle-seconds=-1. No flash-attn
  or KV cache params (embedding models use bidirectional forward pass, not
  autoregressive KV cache). Var: llm_router_nomic_ctx_size.

- roles/llm-inference-multimodel/defaults/main.yml:
  Add llm_router_nomic_ctx_size: 8192.

- host_vars/astro-orbiter/vars.yml:
  Add nomic-embed-text-v1.5-Q4_K_M.gguf to llm_staged_models list
  (size_bytes: 84106624, source: nomic-ai/nomic-embed-text-v1.5-GGUF).
  Update VRAM note to reflect 5 registered models (nomic adds ~84MB,
  negligible given sleep-idle-seconds=-1 / load-on-startup=true pinning).

- playbooks/day2_add_nomic_embed.yml:
  New day2 playbook following the coder-alias pattern:
  Phase 1: idempotent GGUF download (exact size check)
  Phase 2: redeploy preset INI
  Phase 3: redeploy + restart systemd unit
  Phase 4: /v1/models gate (all 5 models present)
  Phase 5: /v1/embeddings smoke test (vector returned, not empty)

VRAM: ~84MB, always pinned. No impact on generative model LRU behavior.
peter-parker Helm values already point at :8002 for the embedding endpoint.

ansible/host_vars/astro-orbiter/vars.yml

@@ -34,21 +34,23 @@ common_root_lv: ubuntu-lv
 # (t_33acbb2e) so the router can keep more than one GGUF resident on-demand
 # and LRU-evict when needed.
 #
-# VRAM NOTE (t_33acbb2e, updated t_55c164f5): With models-max=4 and all 4 GGUFs
-# registered, worst case is all 4 loaded simultaneously:
+# VRAM NOTE (t_33acbb2e, updated t_55c164f5, updated t_34b96e83): With models-max=4 and all 5 GGUFs
+# registered, worst case is all 5 loaded simultaneously:
 #   Qwen3.6-35B-A3B Q4_K_S:           ~21.5GB (weights ~19.5GB + KV ~2GB @ 64K ctx, q4_0)
 #   Phi-3.5-mini-instruct Q8_0:       ~4.3GB  (weights ~3.8GB + KV ~0.5GB @ 32K ctx)
 #   Meta-Llama-3.1-8B Q4_K_M:        ~5.6GB  (weights ~4.6GB + KV ~0.2GB @ 8K ctx)
 #   Qwen2.5-Coder-14B Q4_K_M:        ~9.0GB  (weights ~8.4GB + KV ~0.6GB @ 16K ctx)
-#   Total worst-case:                 ~40.4GB  >>  24GB RTX 3090
+#   nomic-embed-text-v1.5 Q4_K_M:    ~0.09GB (~84MB, embedding only — no KV cache)
+#   Total worst-case:                 ~40.5GB  >>  24GB RTX 3090
 #
 # OOM RISK: Full co-residency is impossible on 24GB. LRU eviction prevents this
-# in practice: models-max=4 means the router can REGISTER 4 models but only keeps
+# in practice: models-max=4 means the router can REGISTER 5 models but only keeps
 # up to 4 LOADED simultaneously — the router will evict the LRU model when a new
-# one is needed. In single-user homelab operation, only one model is active at a
-# time. The realistic maximum co-residency is 2 models (whichever was last used).
+# one is needed. nomic-embed-text-v1.5 is pinned via sleep-idle-seconds=-1 and
+# load-on-startup=true but it uses only ~84MB, so it never meaningfully changes
+# the budget. In single-user homelab operation, only one generative model is active
+# at a time alongside the always-resident embedding model.
 # Qwen3.6-35B alone uses ~21.5GB; co-residency with Coder (~9GB) = ~30.5GB > 24GB.
-# So effectively: Qwen3.6-35B + any second model will OOM IF both are held concurrently.
 # LRU eviction handles this automatically — the router evicts the idle model before
 # loading the new one. Ryan should be aware this means model-switching always incurs
 # a ~30-60s cold-load latency when switching between Qwen3.6-35B and any other model.
@@ -68,4 +70,8 @@ llm_staged_models:
     url: "https://huggingface.co/bartowski/Qwen2.5-Coder-14B-Instruct-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-Q4_K_M.gguf"
     size_bytes: 8988111072
     source_repo: "bartowski/Qwen2.5-Coder-14B-Instruct-GGUF"
+  - filename: "nomic-embed-text-v1.5-Q4_K_M.gguf"
+    url: "https://huggingface.co/nomic-ai/nomic-embed-text-v1.5-GGUF/resolve/main/nomic-embed-text-v1.5.Q4_K_M.gguf"
+    size_bytes: 84106624
+    source_repo: "nomic-ai/nomic-embed-text-v1.5-GGUF"