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
Note recall is asymmetric: a short question goes in, a longer note comes
out. Adds EmbedQuery/EmbedPassage helpers and the e5 prefixes, and points
the note/fact write path at the passage side and the query path at the
query side. Reviewers: the three call sites in voice.go.
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
The most load-bearing decision in the project was stated four incompatible
ways: the docs said Qwen3-1.7B, deploy/mavend.json said Qwen3.5-2B, the repo's
models/llm/ held an LFM2.5-1.2B gguf, and five code comments still said LFM.
Answering "which model is deployed" meant re-deriving it from scratch every
time.
Two facts the review missed, found while resolving it:
- /mnt/hdd1/llms is bind-mounted over /opt/maven/models/llm, which shadows the
repo's models/llm/. The LFM2.5 gguf sitting there was never loaded by
anything, so it was not evidence of the deployed model at all.
- That library holds Qwen3.5-0.8B, -2B and -4B, and no Qwen3-1.7B. The config
pointed at a file that does exist; the docs' Qwen3-1.7B was the stale claim,
the reverse of the assumed direction. Qwen3-1.7B is the CPT target, and that
training is still in flight (Vikunja #122), so no such gguf exists yet.
phraser.model_path moves to Qwen3.5-0.8B (Q4_K_M) — the smallest checkpoint on
disk, chosen for latency, and relevant to whether the LLM router is affordable
on this box. Docs and comments now say the same thing in one voice: 0.8B
resident now, CPT'd Qwen3-1.7B as the target, and the bind-mount shadowing
written down so the next reader does not mistake models/llm/ for ground truth.
Comments name the model, never a filename, so a swap stays a one-line config
change.
n_gpu_layers: 99 is correct and stays — compose passes /dev/dri and the render
gid for Vulkan offload to the Vega iGPU. CLAUDE.md's "CPU-only" was the stale
half of that contradiction and is corrected.
phraser.go also dropped a wrong "sub-1b, prompted not trained" size claim: the
target is trained end-to-end (RU CPT + joint persona/router SFT).
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01X5JApcrCRVGmqrxnhynSik
15 root markdown files, ~4,900 lines against ~33,000 lines of Go, with at least
three pairs contradicting each other. When five documents describe the
architecture, the code becomes the only trustworthy one — which defeats the
point of having them. That drift is why the resident-model question had four
incompatible answers.
SPEC.md, maven.md and ROADMAP.md are deduped into DESIGN.md rather than
concatenated, with a "Superseded" section carrying eight retired decisions and
what replaced each: classifier-owns-the-route (the cascade is still the live
path, but as a stopgap, not a design to extend), faster-whisper/vosk/silero,
the small-model phrasing claim, sqlcipher, the Kotlin/Spring sketches,
obsidian->chroma, script deployment, and FloorEnrollment. Superseded material
is kept and marked rather than deleted, so it cannot read as current.
SESSION-05/06-07-2026.md and PLANS.md are removed outright — git history holds
them, and both were verified tracked before deletion.
Go doc comments citing the deleted files are repointed to the equivalent
DESIGN.md sections. Several asserted designs that were already retired, so the
claims are corrected and not just relinked: stt.go named faster-whisper as
production (it is whisper.cpp), tts.go named silero (it is piper), intent.go
still described the classifier as owning the route, and stale vosk/chroma
vocabulary is replaced. ECOSYSTEM-SPEC.md references are deliberately
untouched — that is a different document, and a naive grep for SPEC.md matches
it.
Root markdown drops from 4,880 to ~3,700 lines. The review's ~1,500 target is
not reachable while keeping the files it also said to keep — those alone are
2,553 lines — so trimming further needs a separate decision on
MAVEN_ECOSYSTEM_ARCHITECTURE.md and PROGRESS.md.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01X5JApcrCRVGmqrxnhynSik
Add a read-only /ecosystem page that consumes the sibling services'
JSON APIs (Nexus entities, Praxis attention, Hexis capabilities),
fetched concurrently with honest per-panel error states. Siblings stay
headless — mavweb is their human surface (arch §16). Wired via mavweb
-nexus/-praxis/-hexis flags; mavweb joins the ecosystem compose network.
Fix mobile horizontal overflow across all pages: .content is a flex
child with default min-width:auto, so it refused to shrink below the
tables' intrinsic width. min-width:0 lets wide tables pan inside .scroll
instead of dragging the page sideways. Verified via CDP geometry check
(scrollWidth === clientWidth at 430px).
Also includes in-progress Ethos UI redesign, ecosystem deploy compose,
and planning docs.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Route contract is now a JSON array of action objects (one per ask) so
compound utterances route all their intents, not just the first. Grammar
root emits `[{intent...},...]`; parseActions tolerates a bare object.
Cascade still returns one Decision — full N-action dispatch lands with the
engine turn-on (marked in-code).
Router prompt rewritten shorter + decision-ordered (prompt-guy feedback),
fact redefined as "implicit update" not "trackable state", kept in Russian
to match the CPT base + phraser. "интент" → "намерение".
CLAUDE.md: routing-architecture section + refreshed open items.
docs/plans: route-data generation plan.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017GMrVfuYN3nE4L1vEiFYC9
Daemon side of Decision B: parse {"response","mood"} across the 4 consumers
(replier, nudges, reminders, chat), fall back to legacy formats. Drop the
LLM router — the classifier handles routing; replier/phraser share one
llm.Client (timeout 20s->60s). llm.Client reads reasoning_content when
content is empty (thinking models).
Docs: TTS piper-student plan (OmniVoice teacher -> piper student, from
scratch, phoneme-first). CLAUDE.md training guide.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Add LLMRouter: grammar-constrained LFM call for intent classification
after stage-0, before classifier cascade. Errors fall through gracefully.
- Add IntentChat: conversational intent with no store side-effect, routed
through LLM -> phraser chat endpoint.
- Extract slots for Chat: no structured slots, full utterance is payload.
- Extend stage-0 grammars to fire through Cyrillic wake-word spellings
(Мэйвен/Мейвен/Майвен/etc.) produced by Russian STT model.
- StripWakeToken helper strips leading wake in any script so time/date
grammars still match when wake is present.
- Add classifier examples for chat utterances (EN + RU).
- Wire LLMRouter into Router.Config; optional, nil-safe.
PythonDateParser shells out to python3 with the dateparser library for
full natural-language date/time extraction. Two-step approach:
1. search_dates() finds the date substring in surrounding text
2. parse() re-parses the substring for correct time resolution
Russian time qualifiers (утра/вечера/дня/ночи) are pre-processed to
AM/PM before parsing — dateparser drops them during substring extraction.
Falls back to StubDateTimeParser when python3 or dateparser isn't
available (graceful degradation, no hard runtime dependency).
Dockerfile updated: python3 + dateparser==1.4.1 in runtime stage.
five fixes spotted during routing investigation:
- gitignore: replace blanket models/ ignore with per-dir exceptions
(/models/embedder/, /models/stt/, /models/tts/) so the seed text
files under models/seeds/ are tracked in version control
- query.txt: fix merged line — 'сколько стоит свет в этом месяце' and
'найди заметку про сервер' were fused with no separator
- reminder.txt: add 11 pure-verb reminder seeds without time expressions
to shift centroid toward the reminding intent rather than time-lexicon
- StubDateTimeParser: add Russian 'через <N> <unit>'/'через час'/'через
полчаса', 'сегодня'/'завтра'/'послезавтра' with optional clock, and
'в <clock>' scan. Add Russian word numbers (один-десять) and unit
inflections (час/часа/часов, минута/минуты/минут, день/дня/дней,
неделя/недели/недель). Also adds missing English day/week units.
- replySystem: guard time branch against duration queries ('сколько
времени прошло') reaching it via the classifier path after the
stage-0 grammar's build filter rejects them. Mirrors stage0.go
duration keywords.
three bugs causing time queries to land on reminder or fact intent:
- seed collision: query.txt and system.txt shared identical time/date
seeds (который час, сколько времени), making system intent
indistinguishable from query intent in centroid space
- threshold (0.35) too low for ONNX embedder — cosine similarities
cluster 0.5-0.7 for related intents, so Clarify never fired
- reminder centroid contaminated by time-lexicon (every seed has a time
expression), pulling any time-word utterance toward reminder intent
fixes:
- remove 3 duplicate time/date seeds from query.txt (keep in system.txt)
- DefaultRouterThreshold 0.35 -> 0.55
- stage-0 grammar for напомни/remind me -> IntentReminder, bypasses
classifier (fixes 'напомни через час' being misrouted to fact)
- stage-0 grammars for time/date system queries (сколько времени,
который час, какой сегодня день) -> IntentSystem, with Build filter
to exclude elapsed/duration queries (сколько времени прошло)
- time parser fallback in applyAction for stage-0 reminder matches
(extractor doesn't run on stage-0 decisions)
- session.go: add History []Turn + Turn type for multi-turn context
- slots.go: add AnaphoraResolver with Resolve() for RU pronoun detection
(это/он/она/оно/тот/мой and inflected forms)
- followup.go: extend followUpMerge with cross-intent inheritance:
Query/Fact/Reminder after a Fact with anaphora inherits the key.
Same-intent path unchanged. Anaphora detection from utterance.
- voice.go: add fact-by-key lookup path in applyAction for IntentQuery
when dialogue resolved an anaphoric reference (calls LatestFact,
formats with formatTime helper). History tracked in Session.History
capped at 4 most recent turns.
- followup_test.go: 7 new test cases: anaphora query-after-fact,
no-inheritance-without-anaphora, three-turn break, anaphora in
reminder, anaphora in fact, explicit key wins, time inheritance.
make test green (303+, -race, all 29 packages).
- Add CalendarEvents method to recordingAPI in auth_test.go
- Add CalendarEvents method to fakeCore in handlers_test.go
Co-Authored-By: opencode <opencode@anthropic.com>
- Stub.PhraseQuery: empty notes → "не знаю." (was: "no notes")
- LLMPhraser.PhraseQuery: empty notes → general knowledge prompt to LLM
- Voice handler: on notes RAG failure, try phraser before giving up
- New router.KnowledgePrompt() pure function with test
Co-Authored-By: opencode <opencode@anthropic.com>
Store: CalendarEvents(ctx, from, to) — filters caldav facts by key date prefix.
IPC: full wiring through interface, server dispatch, and client.
Router: ParseCalendarDate (сегодня/завтра), CalendarEventFormatter (RU reply).
Voice: calendar detection before notes RAG in IntentQuery handler.
Tests: store integration test, date parser tests, formatter tests.
Co-Authored-By: opencode <opencode@anthropic.com>
kami