The querySources order predates the 2026-08-02 ruling that live search leads.
An unconfigured feeds source claimed every news question and answered with a
configuration status, so "что происходит сейчас в новостях про искусственный
интеллект?" never reached the search sitting one source below. It now claims
only when neither SearXNG nor the ZIMs are configured, which is the case the
"не читаю ленты" line was written for — general knowledge would otherwise
invent a bulletin.
The calendar matches on a day word alone and sits above the weather, so
"какая сегодня погода в Москве?" answered "на 02.08.2026 ничего нет." It now
steps aside on weather wording, the same bail-out queryHome already does.
"что нового в лентах?" routed system and answered "пока не умею", while the
same question worded with "новостях" worked. FeedQueryGrammar routes it to
query at stage 0, requiring an ask word and a feed noun so the bare greeting
"что нового?" stays a greeting. Wired in the eval too, since the fixture is
only worth anything while its grammar set is the daemon's.
Also: the claiming source is now logged. /trace is the nudge-rule trace and
carries no query-source field, so a wrong answer could not be told apart from
a wrongly-ordered chain.
Kiwix having no live coverage is filed separately as V-508 — it is a decision
about search quality, not an ordering fix.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Spoken capture was dead. "добавь в задачи купить молоко" routed act, so the
gate found no allowlisted fn and asked "Что сделать?", and the list stayed
empty. Capture rides the note intent by design (#130, no eighth intent), and
nothing under actionNote was reached any more. The model also rewrote the
payload on the way — "купить молоко" came back as "сделать покупку молока",
and a task must read as the words he said.
TaskCaptureGrammar answers it at stage 0, the same place the agenda rules
went. It matches any utterance and lets ParseTaskCapture refuse, so the
marker list stays data. Three phrasings he used are added to that list:
"запиши в список дел" and the two next to it were missing.
The other deterministic matchers were checked for the same exposure. They
are all question-shaped — money, habit, feed, day plan, task list, calendar —
and a question lands on query, which is where they already sit. Capture was
the only imperative among them, which is why only it was taken.
ru-note-006 is the fixture case. The classifier alone cannot pass it, and the
hash baseline drops by that one case; the daemon answers it at stage 0.
"какие планы на сегодня" worked and "какие планы на завтра" answered
"пока не умею": the agenda rule needs "у меня" or a calendar noun, and
that phrasing carries neither. "когда планёрка?" had the same shape.
Two rules. One takes a plan noun aimed at a named day, one takes a closed
list of event nouns after "когда"/"во сколько". Both route intent only,
so the query chain still decides which source answers.
classifier+onnx over the fixture: 55/79, 69.6% full, with the two new
cases passing and no case moving the other way.
Seventeen markdown files at the repo root, twelve of them dated one-shot
reports sitting next to CLAUDE.md. That is why stale docs read as
current: nothing in the path said which was which.
Root now keeps CLAUDE.md and AGENTS.md. Living docs move under docs/
and carry a Last verified line. Dated measurements move to docs/evals/
ISO-prefixed, and are never edited after the day, so a newer number is
a new file. The senior review moves to docs/archive/.
Every reference was rewritten across markdown, Go comments, the Makefile
and the recall fixture. The touched Go packages still build.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
"что у меня сегодня" and "что у меня в календаре сегодня" both routed
IntentSystem on the deployed daemon, and replySystem has no agenda arm,
so both answered "пока не умею". The calendar source that can answer
them lives in the query chain and was never reached. The fixture has
said query since ru-query-019 was written; the daemon disagreed with the
fixture and the daemon was wrong.
AgendaQueryGrammars routes them at stage 0, after the clock rules so
"какой сегодня день" keeps reaching replySystem. Intent only — which
source claims the turn stays the query chain's decision.
This is what made the follow-up continuation look like it only worked
for "what day is it". It did: the query half inherited an intent whose
handler could not answer, so both halves came back "пока не умею".
Measured on the 77-case RU fixture: full accuracy 70.1% → 72.7%,
intent-only 75.3% → 77.9%, calendar 0/2 → 2/2, clarify counts unchanged.
The eval harness wires the new grammars too, or the fixture would stop
being a measurement of the daemon.
Go's \b is ASCII-only and never fires after a Cyrillic letter, which the
first version of the pattern learned the hard way.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TrVSBKe3RFDF4fGYKWYQnX
The phrasing eval printed "llm (0.8B, ...)" no matter which gguf
llama-server had loaded, so two runs of two different models came out
named the same and were easy to mix up when comparing.
It now asks llama-server over /v1/models, same as the router eval
already did. The helper moved to internal/llm so both share it, and it
now errors instead of returning a blank name when the id field is
missing — an unreachable server gets labelled "unknown-model", never a
plausible-looking guess.
Both eval paths stay opt-in behind MAVEN_LLM_URL; no server needed for
go test.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
The prompt named seven intents but never said which one a clock or date
question belongs to, so the model guessed: system->query x4 in every eval
run. The rule now says the clock and the calendar date themselves are
system, what is written in the calendar or in memory stays query, and a
time named inside a request is just part of the request.
That split follows what the daemon can answer. Only replySystem owns the
clock and the date formatter, while the agenda is answered from
CalendarEvents inside the query branch.
Also adds one calendar-agenda fixture case so an over-broad system rule
cannot pass unnoticed, and writes up the before/after numbers. The
targeted confusion is gone; the headline accuracy did not move.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
The 67.1% "thinking off" column in ROUTING-EVAL-31-07-2026.md was an
artefact. It came from a hand-rolled HTTP client in the eval test that
did not send repeat_penalty, so it differed from the reference run on two
axes and the penalty was the one that mattered.
Re-scored back to back on an idle box with everything else held equal:
thinking off is identical to thinking on, case for case, same confusion
matrix, same three unparseable replies. A direct probe of the running
llama-server shows enable_thinking, thinking and reasoning_budget are all
ignored for this model on this build, so there was nothing to turn off.
No defaults changed. The misleading third configuration is removed from
internal/router/eval so its table cannot be quoted again.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
The old model was a symmetric paraphrase model, so it scored "do these
look alike" instead of "does this note answer this question". Also fixes
the file mismatch: the Makefile, the deploy config and both evals now all
name the same quantized file, and the quantized one is what gets measured.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
The bake-off in #278/#250 needs two models' scores side by side, and the
report names only carried the config, so the rows were indistinguishable.
ModelID reads /v1/models instead of taking a string that goes stale.
New target: make eval-models MAVEN_LLM_URL=...
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
Completes #319's comparison. Three configurations, because "the LLM router"
was ambiguous: the model alone, the cascade #320 would actually ship (stage-0
grammar → model → classifier floor), and a thinking-off diagnostic.
intent-only full RU missed-clarify p50
classifier+onnx 36.8% 36.8% 25/61 5/6 31ms
llm-only (0.8B) 48.7% 23.7% 13/61 6/6 850ms
cascade+llm (0.8B) 50.0% 32.9% 18/61 6/6 825ms
On the question asked — does the resident model route better? — yes, 50.0%
vs 36.8% intent accuracy. REARCH.md's premise holds. It costs 27x the
latency (p50 825ms vs 31ms, max 3.1s), on the same llama-server the phraser
needs, so it is a trade rather than a free win.
Three things the numbers surface that the headline hides:
query→fact x15 is the dominant failure, four times the classifier's x4 on
the same axis. routeSystem's decision order puts "сообщает или обновляет
состояние" (rule 3) above "хочет получить информацию" (rule 4), so any
utterance naming a fact key matches the earlier rule and a question about
past state reads as an assertion of it. A prompt fix, not a model limit.
The LLM router cannot clarify: llmrouter.go hardcodes Confidence 1.0, so
stage 3's gate can never fire on its decisions — 6/6 missed. With #359's
finding that the classifier's gate is miscalibrated under ONNX, neither path
currently refuses. Flipping #320 as-is removes the refusal lane.
The gap between 50.0% intent and 32.9% full accuracy is entirely slots: the
LLM path fills neither Fn nor Time (it returns Slots.Text for acts, and
Extract never runs on an LLM decision).
Also settles a hypothesis rather than leaving it in the air: thinking mode is
a non-issue under a grammar (identical score), and the grammar's unbounded
("," ws action)* repetition that ran away in an isolated smoke test does not
reproduce under the real prompt — 2 errors in 76, not 76. internal/llm
deliberately does not grow a chat_template_kwargs field.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01X5JApcrCRVGmqrxnhynSik
The onnxruntime .so was already vendored at deps/onnxruntime-linux-x64-1.26.0
— nothing to download. make eval-router now defaults MAVEN_ONNX_LIB there, so
both baselines run by default and only a fresh clone without deps/ falls back
to the hash ratchet alone.
Prod-representative result, deployed 0.55 gate: 28/76 (36.8%), RU 25/61,
EN 3/15, hard 0/11 → 4/11, p50 31ms / p95 71ms. Versus the hash floor's
13/76 at p50 9µs.
The finding is not the accuracy, it's the refusal lane: missed clarifies went
0 → 5 of 6. Better embeddings raise cosine everywhere, so the 0.55 threshold
that used to hold ambiguous utterances back stops holding — "сделай это"
routes to act at 0.847, "бэкап" to chat at 0.755. The gate was implicitly
tuned to the hash floor's low similarities. That is an argument about the
threshold, not about the embedder, and it lands before #320 rather than after.
Also fixes a fixture-model mismatch: ReminderGrammar deliberately skips the
extractor at stage 0 and the daemon's applyAction parses the time downstream
(stage0.go says so). Charging the router for that slot made 4 exact-match wins
read as misses; they are now counted as SlotsDeferred instead. Hash baseline
moves 13/76, ratchet to 0.15.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01X5JApcrCRVGmqrxnhynSik
#319 asks for a measurement before #320 flips the route decider from the
classifier cascade to the resident model. There was nothing to measure
against: the only routing tests assert single utterances, and the
classifier's seed corpus is its own training set — scoring it there
measures memorisation of frozen centroids, which is the illusion that hid
the weak RU query handling in the first place.
internal/router/eval is a separate package so both paths can be scored
from outside router (including cmd/mavend, where the real llama-server
client lives). The fixture is embedded; the scorer takes a Router
interface, so *router.Router and a bare LLM stage both go through the same
76 cases.
The fixture is a CONTRACT, not a snapshot: cases the cascade fails today
stay in the file and fail loudly. TestFixtureIsHeldOut enforces that no
utterance appears verbatim in models/seeds/*.txt.
Baseline, hash embedder at the deployed 0.55 gate: 9/76 (11.8%), 63 false
clarifies, 0 missed clarifies, p50 9µs. Almost everything falls to the
confidence gate — the documented floor behaviour, not a new bug. The
number worth comparing is TestONNXBaseline's (skipped without
MAVEN_ONNX_LIB); the assertions here are a regression ratchet plus a tight
bound on the dangerous direction: ambiguous utterances must not start
being routed confidently.
Seeding is order-fixed on purpose — a few phrases appear under two intents
and map iteration handed them to a different centroid each run, which made
the score jitter between 9 and 10.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01X5JApcrCRVGmqrxnhynSik
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