A model whose kernels are not upstream needs the fork that has them, and
the ordinary models still want the ordinary build. Anything under
`~/.local/share/ai-app/llama/<name>/` -- `llama-server`, or the
`bin/llama-server` a `cmake --install --prefix` leaves -- is now
discovered beside the one on PATH and becomes a provider called
`llama-cpp-<name>`, with its own router, preset and model settings.
That keeps the module's security property rather than bending it: the
phone still names no command, because what runs is still decided by what
somebody put on the machine. Each probe answer is tagged with what was
asked for, since two of these are now the same program under different
paths.
Flash attention joins the model settings (`flash-attn` in the preset).
llama.cpp's `auto` stays the default; the control is for a model whose
publisher asks for `on` outright, which Prism ML's ternary Bonsai does.
Verified against the fork built into that directory: discovery answers
`llama-cpp-prism`, the child server is started with `--flash-attn on`,
and Ternary-Bonsai-2-27B PTQ1_0 loads and answers through a session.
iris-ai
7e7910083c