Add JustVugg/colibri as a managed engine, mirroring the ds4 integration but
driving the pure-C `colibri` binary DIRECTLY over its stdin/stdout mux protocol
(docs/serve_protocol.md) instead of proxying to a Python gateway — coderai
reproduces openai_server.py's engine client and GLM-5.2 chat template itself.

- config: ColibriConfig (disabled by default; model is a directory container,
  not a GGUF — routes by model_id/alias/name, no arch sniff)
- codai/api/colibri_worker.py: clone+build (make colibri CUDA=1), MuxEngine
  protocol client (READY handshake, SUBMIT/DATA/DONE, KV-slot pool, CANCEL,
  stderr log pump), per-container engine registry
- codai/backends/colibri.py: ColibriBackend + render_chat (byte-exact port of
  colibri's GLM-5.2 template; the engine tokenizes what we send)
- front routing: `colibri` capability on nvidia/cuda/auto; router/assignment/
  app/engine_supervisor thread config.colibri
- manager: colibri_should_handle, backend selection, /v1/models surfacing,
  exclusive-VRAM eviction (wants the whole GPU like ds4)
- admin: config get/set + per-model overrides; settings.html card + models.html row
- packaging: build.sh --colibri, OCI bundle (repo+binary, no 372GB model),
  entrypoint seed, CODERAI_COLIBRI_DIR, smoke test

Ships OFF: no routing changes until colibri.enabled + colibri.model_path are set.
Verified offline: config round-trip, routing predicate, render_chat byte-match
vs colibri's own, MuxEngine end-to-end against a fake engine, CPU engine builds.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LoSpEthysqmseCc6Geizty