Two bugs:
1. run_stream() never merged per-model/server config (think_budget,
temperature, etc.) into the request — unlike run_inner(). Now both
paths apply the same config merge.
2. to_wire() was missing the enable_thinking bool conversion line
(lost in a prior revert). Restored: think_budget=0 → enable_thinking=false.
- A pinned playground model that is unavailable now errors clearly instead of
silently answering from the managed local model (route_source no longer lies).
- The managed CMF model is surfaced in GET /admin/api/models (marked "managed",
shown read-only in the UI) so the real running model is visible and pinnable
without a hand-maintained [[models]] entry; a fresh install still lists nothing.
- Deleting a model now removes its local .cmf physically (file or tensor-dir);
deleting the managed model also stops the server and clears the [cmf] config.
Routing is stripped of the deleted id so the config still validates.
- import.rs / promotion.rs: sort_by(|a,b| b.k.cmp(&a.k)) -> sort_by_key(Reverse(k))
- pipeline.rs: skip_while(!p).next() -> find(p)
Behaviour-preserving; completes the CI fix started by the cargo fmt commit.
Run models in the CMF (.cmf) format locally, via the native `cortiq`
CLI from crates.io — no Python and no external model server.
- cmf_runtime: install/update `cortiq-cli` from crates.io, spawn and
health-check `cortiq serve` as a managed local backend.
- import: model-import jobs shell out to the native `cortiq convert`
(HF repo -> .cmf, quant mapped Q8_2F->q8_2f / Q8_ROW->q8 / Q4->q4);
the Python converter is used only for advanced/exotic options.
- pipeline: local-first routing — serve from the local CMF model when
the router is disabled/unreachable, with a "local only" hard switch.
- registry/state: register the local CMF server as an OpenAI provider
and track local candidates.
- config: data-dir resolution + CmfCfg (auto-install/update, managed
server, host/port/model) and relaxed validation for the managed model.
- admin + settings UI (en/ru): "Local models (CMF)" settings card.
- cache.rs: cosine-similarity store (threshold, TTL, ring buffer), partitioned by
routing signature; tracks hit rate and model cost saved
- pipeline: embed routing text, look up before the model call (route_source=cache on
hit), insert successful responses; stats record cache hits
- config [cache] + admin settings card; dashboard shows hit-rate and savings
- embedding model resolved from the pool (or first kind="embedding")
infosave2007