cluster: nodes as engines, one GGUF over llama.cpp RPC, vLLM/SGLang multi-node, pools, compat-filtered model form

Several coderai installs as one:

- Cluster nodes (cluster.nodes): another install is an engine of this front —
  polled on its /cluster/state, assigned models, pinned by name, routed by
  capability and load; entries pushed to /cluster/reload-config and localized
  there; Load/Unload reach it through token-guarded twins. Live add/remove.
- llama.cpp RPC: codai/backends/ggml_rpc.py registers rpc-server endpoints
  through ctypes and gives every load an explicit device list (local cards,
  then the model's rpc_servers); the split and the VRAM pool see remote
  memory. cluster.rpc_servers runs this machine's rpc-server processes;
  packaging/build-rpc-server.sh builds it from the vendored llama.cpp;
  build.sh and the images build llama-cpp-python with GGML_RPC.
- vLLM on Ray (pipeline parallel across nodes) and SGLang --nnodes: per-model
  vllm/kt blocks over the global config, node start/stop commands, ray head
  and worker mode in boot.sh.
- Pools: several URLs per capability remote and several machines per host
  model, with failover.
- Models page: engine/backend selects narrowed live to compatible pairs,
  impossible pairs refused; Settings → Cluster; /admin/cluster page.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FKm7Z56iKjHgNkHc6VhWKz