embedder.heads_path is empty by default and deploy/mavend.json sets
it. A missing or broken weights file logs and leaves the heads nil,
because refusing to start over a routing accelerator would trade a
working box for a better one.
TestONNXRoutingHeads is the same cascade TestONNXBaseline scores with
one arm added, so the two are directly comparable. It also checks the
Go tokenizer against the Python one, since the heads were trained
through transformers and are read through a hand-written tokenizer: a
mismatch shows up here as a score below what Python measured on the
same weights, and nowhere else. That is how the reversed word pieces
were found.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_013ptwopxyo3Z2kwFckHkLvN
The review comment asked for basic DI. The answer is the idiom voice.go
already had for capabilities — a cohesive *Wiring struct — applied to a
group that is not a capability toggle, plus the decision written down so
it is a rule and not a habit.
recallWiring holds the embedder, the vector store, the personal boundary
and the two numbers that gate an answer. They sat in three places on
reactiveHandler, with the gate numbers a hundred lines from the store
they gate. Its zero value means no recall, so it is a value, not a
pointer like the optional-capability groups.
dataStore stays out of it. patterns.go, ecosystem_acts.go and confirm.go
use it, so it is not part of this cluster.
docs/handler-wiring.md records the choice, rejects a container or a
wire-style generator outright, defers narrow per-handler interfaces to
the package split that would justify them, and states the constraint the
task named: a wiring change does not ride a feature PR.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
WriteFactReq gains an optional Subject field (empty = old behavior,
no CoreAPI signature change) and the IntentFact handler now passes the
fact's key as its resolution subject, so voice-tapped facts flow into
the Vikunja #279 enrichment queue automatically.
Also: deploy/mavend.json's phraser was pointed at a 4B model with
n_gpu_layers=99, which OOM'd under memory pressure and left a zombie
llama-server child. Swapped to the 2B Qwen model matching the intended
resident-model size, keeping GPU offload.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018ghELqYhZNLub2TXGMazqA
claude
kami