vLLM was installed by hand and named in each agent's configuration. The
agent now installs it: a Python 3.12 environment built by uv, which is
itself a GitHub release checked against its checksum, from PyPI resolved as
it stood a day after that vLLM was published and installed with
--require-hashes. The resolved list is kept in the environment. The
environment is built relocatable under a scratch name and renamed into place
once it runs, like an archive.
The default is 0.30.0, whose flags were checked against the ones llmgw
builds. It is built for CUDA 13, so it needs driver 580 and a Turing GPU or
newer, and 25 GB free while it installs; a node lacking one says which, and a
node with no GPU skips it without being shown as a fault. gcc comes with it
because Triton compiles its launcher at the first model load. SGLang
installs the same way when the control plane names a version. llmgw doctor
reports whether vLLM can be installed on the node.
Checked by installing 0.30.0 this way on a test node: 7.7 GB, torch 2.13 for
CUDA 13.0, importing cleanly; the node has no GPU, so vLLM was not started.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The agent's defaults said eth0 before normalize looked for the interface
holding the management address, so it never looked: a node on ens3 or
bond0 had NCCL and Gloo bootstrap over an interface it does not have. It
is now found, with eth0 only as the last resort.
The agent unit sets LimitMEMLOCK=infinity. RDMA pins what it registers,
and under systemd's 8 MB default an engine without the capability that
lets root ignore the limit fails its first collective over InfiniBand.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
server init now also:
- runs a model mirror beside the control plane (/srv/models, bytes on
:8081 at an address nodes reach, management API on loopback so it
needs no certificate) and adds it to server.yaml;
- makes the machine a node of its own control plane: issues its agent
certificate, writes agent.yaml labelled as the control plane, starts
llmgw-agent, and waits for it to register and install llama.cpp;
- checks for NVIDIA GPUs with nvidia-smi, and reports a card on the PCI
bus whose driver does not answer rather than ignoring it;
- fetches Qwen2.5 0.5B (Q4_K_M) into the mirror and adds it to the
catalog pinned to this node: a llama.cpp profile per GPU class found,
with a CPU profile as the fallback, then waits for it to serve.
--no-mirror, --no-node and --no-model leave these out. Every step looks
before it acts, so a rerun finishes what an interrupted one started.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
