feat(llm-inference-multimodel): bump router --models-max 1->4 on astro-orbiter (t_33acbb2e)

Changes:
- host_vars/astro-orbiter/vars.yml: add llm_router_models_max: 4 (overrides
  conservative default of 1). Detailed VRAM OOM risk note included inline:
  worst-case 3-model co-residency ~31GB > 24GB RTX 3090. LRU eviction
  mitigates in single-user operation; flagged for Ryan's review.
- playbooks/day2_bump_router_models_max.yml: new targeted playbook; deploys
  updated router unit, restarts the live service, verifies /health 200 and
  /v1/models lists all 3 GGUFs post-restart.
- group_vars/all/semaphore.yml: add llm_router_update_unit template pointing
  at the new playbook.
- roles/llm-inference-multimodel/defaults/main.yml: update comment to reflect
  the var is now overridden in host_vars rather than 'hardcoded to 1'.
- roles/llm-inference-multimodel/templates/llama-server-router.service.j2:
  correct stale 'HARDCODED TO 1' comment — value is variable-driven.

Constraints honored:
- --parallel 1 left untouched (not in scope, not modified anywhere)
- No ad-hoc SSH/systemctl/curl state mutation; all execution via Semaphore
- No installed/vendored code patched

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

@@ -107,8 +107,9 @@ llm_existing_gemma_service_name_guess: llama-server
 # Default: llm_router_enabled: false — all router tasks are no-ops until you
 # flip this to true (either in host_vars, extra-vars, or the shadow playbook).
 #
-# CRITICAL: llm_router_models_max is hardcoded to 1 in the j2 template AND
-# listed here for documentation. DO NOT raise it without a VRAM budget review.
+# CRITICAL: llm_router_models_max default is 1 here for safety. It is
+# overridden to 4 in host_vars/astro-orbiter/vars.yml (t_33acbb2e) with
+# a full VRAM budget note. DO NOT raise it without a VRAM budget review.
 # Default llama-server cap is 4 simultaneous — that would OOM a 24GB card
 # immediately when Qwen3.6-35B (20GB) is the resident model.
 #