A pod cannot see this machine's disk, so "use my local models on RunPod"
needed a way for the pod to GET them. Three, now, picked by `source`:

  auto   — an explicit hf_repo, a path that already is a repo id, or a
           repo id recovered from the HuggingFace cache path
           (models--Owner--Repo). Most of a normal catalogue resolves
           with nothing typed: weights downloaded through coderai live
           in that cache, and the directory name still says where from.
  hf     — download hf_repo from HuggingFace.
  url    — download model_url directly, which is how most one-off GGUFs
           are had.
  upload — send the weights from here.

Each server gets only what it can use, refused at configuration time
rather than after five minutes of pod boot: vLLM is launched `--model`
and takes a repo id only; llama.cpp takes `-hf` or downloads a URL with
`-mu`; upload works only on a coderai pod, because vLLM and llama.cpp
need the file before their container starts while a coderai pod loads
models on demand.

Upload is a real option, not a token one — on symmetric gigabit a 30 GB
model is a few minutes — but it is the cold cost of every NEW pod, so it
is never chosen automatically. /v1/models/upload streams to disk in
chunks (never into memory), extracts a tar for multi-file models with
every member checked against the destination, and registers the entry in
memory only. An existence check by name and size makes a repeat free and
refuses a half-copy.

keep_warm keeps one pod running so nothing waits for a cold boot. OFF by
default and deliberately: a warm pod bills every hour of every day,
including the ones nobody uses it. Warm pods start at startup, since a
pool created on first use would still pay the boot it exists to avoid.

All of it is in the UI: weights source with the right field shown per
choice, keep-warm, and an "always run this model locally" pin.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0182DhR1eFNPQyGmDrpHbedY