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/roles/llm-inference-multimodel/defaults/main.yml

@@ -160,3 +160,8 @@ llm_router_phi_flash_attn: "{{ llm_router_flash_attn }}"
 llm_router_coder_ctx_size: 16384
 llm_router_coder_flash_attn: "true"
 llm_router_preset_path: /opt/llama-server-router-preset.ini
+# nomic-embed-text-v1.5: embedding model, ctx-size=8192 per task t_34b96e83
+# No flash_attn or KV cache params — embedding models use bidirectional forward pass,
+# not autoregressive KV cache. load-on-startup=true / sleep-idle-seconds=-1 keep it
+# always warm at negligible VRAM cost (~84MB).
+llm_router_nomic_ctx_size: 8192