End-to-end serverless: a model tagged backend:runpod (mode:serverless) proxies
OpenAI chat/completions to a RunPod serverless endpoint. Runs on a remote GPU,
holds NO local weights.

- codai/api/runpod_worker.py: RunpodModelConfig + parse_model_runpod (mode/pools/
  criteria/gpu/price/scaling/cost/serverless), serverless_base_url + auth_headers.
- codai/backends/runpod.py: RunpodBackend — thin OpenAI proxy (chat/stream, Bearer
  auth for serverless), uses_local_vram=False; pods/auto raise a clear "next phase"
  error for now.
- manager.py: runpod in _ENGINE_BACKENDS + _runpod_name_claims (pin-only) +
  runpod_should_handle + load_model dispatch branch. _model_is_runpod() gate:
  set_default_model skips local download/cache for runpod-served models.
- router.py + registry.py: runpod is an explicit-pin capability; added to every
  engine's default caps (no local VRAM → any node hosts the proxy; prefers primary).
- admin routes: whitelist per-model `runpod` + `runpod_spillover` blocks; skip
  local-VRAM estimate for runpod models.
- models.html: RunPod backend option + full per-model sub-form (mode w/ explainer,
  serverless endpoint, served model, pools/criteria/gpu/price/spot, min/max pods,
  idle timeout, image/disk/port/env, spend limit+period) + prefill/collect.

Serverless verified wired in-image (ef1fd7a3802c). Pods pool/scaler, cost ledger,
spillover routing, and stats UI are later phases.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01R6iugoNeEgt9PkajKrFyq4