Merge remote-tracking branch 'origin/master' into task/486-deploy-the-workstation-transcriber

This commit is contained in:
2026-08-09 01:22:03 +04:00
27 changed files with 1411 additions and 32 deletions
+30 -3
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@@ -343,9 +343,36 @@ the possessive agenda rules claim those cases at stage 0 and name nothing, so no
label reaches the head. That is the same trade V-660 flagged and it wants the
owner's call.
**Nothing of this runs in Go.** The weights are `heads.pt` and `out/body_heads/`
on workpc. Reaching the daemon needs an ONNX export and a caller. The resident
e5-small must not be replaced by the copy, because recall depends on that file.
**The heads run in Go and route every turn, since 08-08-2026** (V-664,
`docs/evals/2026-08-08-routing-heads-in-go.md`). This section used to say
nothing of it ran. `RouterHeads` in `internal/router/heads.go` loads
`router_heads.onnx` and reads intent, destination and clarify off one forward
pass. It is stage 0b: after the grammars, **before** the resident model, and the
classifier is still behind both. Through the cascade it scores intent **96.9%**
and destination **75.8%** at p50 27.9ms. That beats the gemma-4-12b cascade,
84.4% and 72.7%, at a twelfth of its 329ms. The workstation stays the better
phraser and is no longer the better router.
Three rules around it. The **clarify head decides first**, before the intent
threshold. It answers a different question. A thin utterance scores low
intent by construction, so gating it cost 6 of 8 ambiguous cases. The
**destination head is read on `IntentQuery` only**, since no other intent
reaches `queryWalk`. And `headsThreshold` is 0.6, the measured knee: every value
to 0.85 drops right answers and keeps the same two wrong ones.
`voice.embedder.heads_path` is the whole switch. Empty, missing or unloadable
means the heads are nil and the cascade is byte-for-byte what shipped before
them. **It must never be pointed at `model_path`.** The resident e5-small must
not be replaced by the fine-tuned copy. Recall depends on that file scoring
what it scored.
**The hand-written tokenizer read every long word backwards** until this task
(`encodeWord`, `onnxembedder.go`). It cost recall@1 7.4 points and recall@3 11.1.
Nothing caught it because seeds and queries were mangled the same way, so cosine
survived. The heads found it. They are trained through transformers and read
through this. The embedder id now carries a tokenizer revision
(`@384/tok2`), so fixing the tokenizer triggers `ReembedAll` the way swapping the
model file does. Bump `tokenizerRev` on any change to what it emits.
`Confidence: 1.0` used to be hardcoded in `llmrouter.go`, so the LLM
path could never ask for clarification (6/6 refusal cases missed on the fixture) — Vikunja
+1 -1
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@@ -19,7 +19,7 @@ func TestChatAnswersWithNoLlamaServer(t *testing.T) {
dead := llm.New("http://127.0.0.1:1", 500*time.Millisecond)
emb := router.NewHashEmbedder(1024)
h.recall.embedder = emb
h.router = buildRouter(emb, h.matcher, 0.55, pickLLMRouter(true, dead))
h.router = buildRouter(emb, h.matcher, 0.55, pickLLMRouter(true, dead), nil)
h.replier = newLLMReplier(dead, nil)
ctx := withDialogueID(context.Background(), dialogueIDFor(sourceText, "web"))
+2 -2
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@@ -317,7 +317,7 @@ func TestClarifyExpiryIsAnnouncedAndWordsStillRoute(t *testing.T) {
h, _, now := newClarifyHandler(t)
emb := router.NewHashEmbedder(1024)
h.recall.embedder = emb
h.router = buildRouter(emb, h.matcher, 0.55, nil)
h.router = buildRouter(emb, h.matcher, 0.55, nil, nil)
if _, asked := h.askClarify(ctx, clarifyDec(router.IntentReminder, router.Slots{Text: "напомни"}, "напомни")); !asked {
t.Fatal("expected a question")
@@ -671,7 +671,7 @@ func TestUnresolvedActSaysItDoesNotKnowTheCommand(t *testing.T) {
func newRoutingClarifyHandler(t *testing.T) (*reactiveHandler, *store.Store) {
t.Helper()
h, st, _ := newClarifyHandler(t)
h.router = buildRouter(router.NewHashEmbedder(1024), h.matcher, 0.55, nil)
h.router = buildRouter(router.NewHashEmbedder(1024), h.matcher, 0.55, nil, nil)
h.recall = recallWiring{embedder: router.NewHashEmbedder(1024), memStore: memory.NewInMemoryStore()}
return h, st
}
+1 -1
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@@ -25,7 +25,7 @@ func traceHandler(t *testing.T, ring *decision.Ring) *reactiveHandler {
return &reactiveHandler{
api: api,
recall: recallWiring{embedder: emb, memStore: memory.NewInMemoryStore()},
router: buildRouter(emb, tool.NewMatcher(api), 0.55, nil),
router: buildRouter(emb, tool.NewMatcher(api), 0.55, nil, nil),
replier: voice.NewStubReplier(),
now: func() time.Time { return now },
dataStore: st,
+1 -1
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@@ -171,7 +171,7 @@ func newDialogueHandler(t *testing.T) (*reactiveHandler, *store.Store, *time.Tim
// and never a coincidence (V-577, V-579). checkEnd refuses any reminder
// landing on it, and at 09:00 the row that answers "на 9" would trip that.
*now = time.Date(2026, 7, 31, 9, 17, 0, 0, time.UTC)
h.router = buildRouter(router.NewHashEmbedder(1024), h.matcher, 0.55, nil)
h.router = buildRouter(router.NewHashEmbedder(1024), h.matcher, 0.55, nil, nil)
h.recall = recallWiring{embedder: router.NewHashEmbedder(1024), memStore: memory.NewInMemoryStore()}
return h, st, now
}
+1 -1
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@@ -24,7 +24,7 @@ func TestApplyAction_FactCapture_QueuesEntityResolution(t *testing.T) {
emb := router.NewHashEmbedder(1024)
matcher := tool.NewMatcher(api)
rtr := buildRouter(emb, matcher, 0.55, nil)
rtr := buildRouter(emb, matcher, 0.55, nil, nil)
h := &reactiveHandler{
api: api,
+1 -1
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@@ -20,7 +20,7 @@ func newFactGateHandler(t *testing.T, now time.Time) (*reactiveHandler, ipc.Core
h := &reactiveHandler{
api: api,
recall: recallWiring{embedder: emb, memStore: memory.NewInMemoryStore()},
router: buildRouter(emb, tool.NewMatcher(api), 0.55, nil),
router: buildRouter(emb, tool.NewMatcher(api), 0.55, nil, nil),
replier: voice.NewStubReplier(),
now: func() time.Time { return now },
dataStore: st,
+1 -1
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@@ -45,7 +45,7 @@ func newNoteHandler(t *testing.T) (*reactiveHandler, *store.Store) {
h := &reactiveHandler{
api: api,
recall: recallWiring{embedder: emb, memStore: memory.NewInMemoryStore()},
router: buildRouter(emb, tool.NewMatcher(api), 0.55, nil),
router: buildRouter(emb, tool.NewMatcher(api), 0.55, nil, nil),
replier: voice.NewStubReplier(),
now: func() time.Time { return now },
dataStore: st,
+2 -2
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@@ -22,7 +22,7 @@ func TestReactiveNotesReminders(t *testing.T) {
emb := router.NewHashEmbedder(1024)
matcher := tool.NewMatcher(api)
rtr := buildRouter(emb, matcher, 0.55, nil)
rtr := buildRouter(emb, matcher, 0.55, nil, nil)
h := &reactiveHandler{
api: api,
@@ -104,7 +104,7 @@ func TestSpokenTaskCaptureFilesATask(t *testing.T) {
h := &reactiveHandler{
api: api,
recall: recallWiring{embedder: emb, memStore: memory.NewInMemoryStore()},
router: buildRouter(emb, matcher, 0.55, nil),
router: buildRouter(emb, matcher, 0.55, nil, nil),
replier: voice.NewStubReplier(),
now: func() time.Time { return now },
dataStore: st,
+1 -1
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@@ -474,7 +474,7 @@ func newSimWorld(t *testing.T, sc scenario) *simWorld {
// used to be built on a nil API, which meant any scenario that produced an
// act panicked the moment the matcher was consulted.
matcher := tool.NewMatcher(api)
rtr := buildRouter(emb, matcher, config.DefaultRouterThreshold, router.NewLLMRouter(scripted))
rtr := buildRouter(emb, matcher, config.DefaultRouterThreshold, router.NewLLMRouter(scripted), nil)
w.handler = &reactiveHandler{
stt: simTranscriber{},
+43
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@@ -0,0 +1,43 @@
package main
import (
"testing"
"github.com/kami/maven/internal/config"
"github.com/kami/maven/internal/stt"
)
// A box with no workstation.stt block transcribes exactly as it did before the
// seam existed: the floor is handed back untouched, and nothing probes.
func TestSttSeamWithNoBlockIsTheFloor(t *testing.T) {
floor := stt.NewStub()
got, pair := sttSeam(&config.Config{}, floor)
if pair != nil {
t.Fatal("no block must build no pair")
}
if got != stt.Transcriber(floor) {
t.Fatal("no block must hand back the floor itself")
}
}
func TestSttSeamPrefersTheWorkstation(t *testing.T) {
cfg := &config.Config{Workstation: &config.WorkstationConfig{
URL: "http://127.0.0.1:1",
Stt: &config.WorkstationSttConfig{
URL: "http://127.0.0.1:2/transcribe",
Health: "http://127.0.0.1:2/health",
},
}}
got, pair := sttSeam(cfg, stt.NewStub())
if pair == nil {
t.Fatal("a configured block must build a pair")
}
defer pair.Stop()
if got != stt.Transcriber(pair) {
t.Fatal("the pair is what callers must transcribe through")
}
// Nothing answers on port 2, so the seam is the floor until it does.
if pair.Available() {
t.Fatal("an unreachable workstation must not be available")
}
}
+76 -4
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@@ -36,7 +36,9 @@ type voiceWiring struct {
sessions *voice.Sessions
voiceSink delivery.Sink
embedder router.Embedder
handler *reactiveHandler // the reactive handler for IPC Chat
// heads — the routing heads, nil unless embedder.heads_path is set.
heads *router.RouterHeads
handler *reactiveHandler // the reactive handler for IPC Chat
// worker clients (set when configured as Remote): closed on shutdown so
// mavsttd / mavttsd don't keep a stale conn into a restarting daemon.
sttClient *worker.Client
@@ -53,7 +55,11 @@ type voiceWiring struct {
// unless a `workstation` block names an address. Held here only so the
// prober is stopped on shutdown; callers were handed it at build time.
pair *llm.Pair
mcp *mcpWiring
// sttPair — CrisperWhisper 2.0 on the workstation with mavsttd as the
// floor, nil unless the `workstation.stt` block names an address. Held for
// the same reason as pair: to stop its prober on shutdown.
sttPair *stt.Pair
mcp *mcpWiring
// home — the Home Assistant client, nil unless the `smarthome` block is
// enabled (Vikunja #256). Its devices land in the same allowlist as every
// other act, so nothing else here has to know about it.
@@ -72,6 +78,9 @@ func (w *voiceWiring) close() {
if w.embedder != nil {
_ = w.embedder.Close()
}
if w.heads != nil {
_ = w.heads.Close()
}
if w.server != nil {
_ = w.server.Close()
}
@@ -84,6 +93,9 @@ func (w *voiceWiring) close() {
if w.pair != nil {
w.pair.Stop()
}
if w.sttPair != nil {
w.sttPair.Stop()
}
w.mcp.close()
}
@@ -112,6 +124,7 @@ func wireVoice(cfg *config.Config, coreAPI ipc.CoreAPI, phr phraser.Phraser, mem
} else {
transcriber = stt.NewStub()
}
transcriber, w.sttPair = sttSeam(cfg, transcriber)
w.transcriber = transcriber
// ----- tts (Stub in-process OR Remote) -----
@@ -147,6 +160,24 @@ func wireVoice(cfg *config.Config, coreAPI ipc.CoreAPI, phr phraser.Phraser, mem
emb = router.NewHashEmbedder(1024)
}
w.embedder = emb
// ----- router: routing heads (only when configured, and never fatal) -----
// A missing or broken weights file logs and leaves w.heads nil, which is
// byte-for-byte the cascade that shipped before V-664. Refusing to start
// over a routing accelerator would trade a working box for a better one.
if cfg.Voice.Embedder != nil && cfg.Voice.Embedder.HeadsPath != "" {
h, err := router.NewRouterHeads(
cfg.Voice.Embedder.HeadsPath,
cfg.Voice.Embedder.TokenizerPath,
)
if err != nil {
log.Printf("voice: routing heads unavailable, cascade unchanged: %v", err)
} else {
log.Printf("voice: routing heads loaded from %s", cfg.Voice.Embedder.HeadsPath)
w.heads = h
}
}
repairFactVectors(dataStore, emb)
checkStoredEmbedder(dataStore, emb)
// Retention is enforced on write, which is not enough on its own: a box that
@@ -223,7 +254,8 @@ func wireVoice(cfg *config.Config, coreAPI ipc.CoreAPI, phr phraser.Phraser, mem
// against the classifier's 50.0%, at about 1s a turn instead of 30ms (see
// config.VoiceConfig.LLMRouter). The classifier always stays wired as the
// fallback, so a model error never breaks a turn.
rtr := buildRouter(emb, matcher, threshold, pickLLMRouter(cfg.Voice.UseLLMRouter(), hot))
rtr := buildRouter(emb, matcher, threshold,
pickLLMRouter(cfg.Voice.UseLLMRouter(), hot), w.heads)
// ----- sessions registry (shared with voicesink) -----
sessions := voice.NewSessions()
@@ -366,6 +398,44 @@ func modelSeam(cfg *config.Config, resident *llm.Client) (router.Completer, *llm
return pair, pair
}
// sttSeam builds the transcription seam the voice path and the meeting
// recorder share. It is modelSeam for audio and follows the same rule.
//
// With no `workstation.stt` block it hands back the floor untouched, which is
// today's deploy exactly. With one, it is an stt.Pair preferring CrisperWhisper
// 2.0 on workpc, which scores 10.4% WER in Russian against the floor's 27.5%
// (docs/evals/2026-08-09-crisperwhisper2-russian-wer.md).
//
// Only the silent half of the degradation rule applies here. A worse transcript
// is still a turn, so there is nothing to name a gap about and the fallback is
// never spoken. That is why stt.Pair has no TranscribeRemote.
func sttSeam(cfg *config.Config, floor stt.Transcriber) (stt.Transcriber, *stt.Pair) {
if cfg.Workstation == nil || cfg.Workstation.Stt == nil {
return floor, nil
}
s := cfg.Workstation.Stt
lang := ""
if cfg.Voice != nil {
lang = cfg.Voice.Lang
if cfg.Voice.Stt != nil && cfg.Voice.Stt.Lang != "" {
lang = cfg.Voice.Stt.Lang
}
}
pair := stt.NewPair(
stt.NewHTTPTranscriber(s.URL, s.Token, lang, time.Duration(s.Timeout)),
floor,
s.Health,
time.Duration(s.Probe),
)
pair.Start(context.Background())
if s.Token == "" {
log.Print("voice: the workstation transcriber has no token, so anything on the LAN can post audio to it")
}
log.Printf("voice: workstation transcriber at %s, probed every %s, mavsttd as the floor",
s.URL, time.Duration(s.Probe))
return pair, pair
}
func pickLLMRouter(enabled bool, c router.Completer) *router.LLMRouter {
if !enabled {
return nil
@@ -390,7 +460,8 @@ func pickLLMRouter(enabled bool, c router.Completer) *router.LLMRouter {
// intent from seedDir (models/seeds/<intent>.txt) — see seedClassifier
// below for the current intent list and file names.
// - Threshold is from voice.router_threshold config (default 0.55).
func buildRouter(emb router.Embedder, acts router.ActMatcher, threshold float64, llmR *router.LLMRouter) *router.Router {
func buildRouter(emb router.Embedder, acts router.ActMatcher, threshold float64,
llmR *router.LLMRouter, heads *router.RouterHeads) *router.Router {
cls := router.NewClassifier(emb)
seedClassifier(cls)
grammars := router.DefaultGrammars(acts)
@@ -442,6 +513,7 @@ func buildRouter(emb router.Embedder, acts router.ActMatcher, threshold float64,
},
Threshold: threshold,
LLM: llmR,
Heads: heads,
})
}
+2 -1
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@@ -251,7 +251,8 @@
"embedder": {
"model_path": "/opt/maven/models/embedder/multilingual-e5-small/model_quantized.onnx",
"tokenizer_path": "/opt/maven/models/embedder/multilingual-e5-small/tokenizer.json",
"lib_path": "/opt/maven/lib/libonnxruntime.so"
"lib_path": "/opt/maven/lib/libonnxruntime.so",
"heads_path": "/opt/maven/models/embedder/router-heads/router_heads.onnx"
},
"llm_router": true,
"query_min_score": 0.55,
@@ -0,0 +1,146 @@
# The routing heads, running in Go
Date: 2026-08-08. Vikunja V-664.
Weights: `router_heads.onnx`, fp32, exported from `heads.pt` on workpc.
Fixture: `internal/router/eval/ru_routing_v1.json`, 96 cases, 33 carrying a destination.
Runner: `make t PKG=./internal/router/eval/ RUN=TestONNXRoutingHeads`.
The four heads of V-661 ran nowhere. This is the number they score through the
Go cascade. Same fixture and same grammars as `TestONNXBaseline`, and only the
middle stage varies.
## Headline
| | classifier + ONNX | heads + classifier | gemma-4-12b cascade |
|---|---|---|---|
| intent | 75.0% (72/96) | **96.9% (93/96)** | 84.4% |
| destination | 33.3% (11/33) | **75.8% (25/33)** | 72.7% |
| false clarify | 0 | 1 | 2 |
| missed clarify | 8 | 1 | 1 |
| p50 | 24.5ms | 27.9ms | 329ms |
A 118M encoder beats the 12B teacher it was distilled from. It wins on both
halves of the route, at a twelfth of the latency. The workstation stays the
better phraser and is no longer the better router.
The p50 is not the heads. Most of it is the classifier's own embedder pass on
the turns the heads decline, plus process warm-up on the first case. The heads'
own forward pass measures 7.3ms on workpc.
## Two defects were in the way, and the first was not in the heads
**The tokenizer read every long word backwards.** `encodeWord` backtracks the
Viterbi path from the end of a word and prepends each piece. That puts them back
in reading order, and a second reverse after the loop undid it. So
`query: вода` tokenized to `[0 12 1294 41 12489 2]` where the reference
tokenizer gives `[0 41 1294 12 12489 2]`.
It was found here and only here. The heads were trained through transformers and
are read through the hand-written tokenizer. So a mismatch shows up as a score
far below what Python measured on the same weights. Nothing else in the suite
compares the two.
Measured on the recall fixture, same 27 cases either way:
| | reversed | fixed |
|---|---|---|
| recall@1 | 70.4% (19/27) | **77.8% (21/27)** |
| recall@3 | 85.2% (23/27) | **96.3% (26/27)** |
| answered after gate | 63.0% | 66.7% |
| wrong note on top | 8 | 6 |
| false recall | 0/5 | 1/5 |
The classifier barely moved, 76.0% to 75.0%, and destination 36.4% to 33.3%.
Both are one case on 96 and neither is a finding. Seeds and queries were mangled
the same way, so cosine survived it. Recall is where it cost, because a stored
passage and a live query are different lengths and break differently.
The one new false recall is the honest cost and it is not being hidden. A
sharper embedder scores every candidate higher, including the ones that should
have stayed under the gate. That is the same trade `2026-08-04-recall-e5-small.md`
recorded when e5-small replaced MiniLM.
The embedder id now carries a tokenizer revision, `model_quantized@384/tok2`.
Stored vectors were written under rev 1 and no longer sit in the same space as a
query embedded now. The model file's name never moved, so nothing would have
triggered `ReembedAll`. On the box the marker fired on start, and the re-embed
rewrote 65 notes and 19 facts in 5 seconds.
**The clarify head was being thrown away.** It was read only when the intent head
cleared its own threshold. That cost 6 of the 8 ambiguous cases. `вода` reads as intent
`act` at 0.233 and clarify at 0.983. Burying that handed the turn to the
classifier, which routed it confidently and never asked. The clarify head answers
a different question, which is whether there is enough here to act on at all. So
it decides on its own and decides first.
| | intent-gated | clarify decides first |
|---|---|---|
| intent | 90.6% | 96.9% |
| missed clarify | 7 | 1 |
| false clarify | 0 | 1 |
## The threshold is measured, not chosen
Max softmax over the intent head, on the 88 cases carrying an intent:
| threshold | kept | accuracy kept | wrong kept | right dropped |
|---|---|---|---|---|
| 0.5 | 84 | 96.4% | 3 | 2 |
| **0.6** | **81** | **97.5%** | **2** | **4** |
| 0.7 | 75 | 97.3% | 2 | 10 |
| 0.8 | 64 | 96.9% | 2 | 21 |
| 0.9 | 46 | 100.0% | 0 | 37 |
0.6 is the knee. Every value from 0.7 to 0.85 drops right answers and keeps the
same two wrong ones. 0.9 is the only value that clears them, and it costs 37
correct routes to do it.
## Quantization was measured and rejected
| build | size | intent | destination | p50 |
|---|---|---|---|---|
| fp32 | 470MB | 83/88 (94.3%) | 28/33 (84.8%) | 7.3ms |
| int8 | 118MB | 79/88 (89.8%) | 26/33 (78.8%) | 4.0ms |
| fp16 | 235MB | will not load | — | — |
Python numbers, on the heads alone rather than through the cascade. int8 costs
4.5 points of intent and 6 of destination to save 3ms. The cascade around it has
a p50 over a second when the resident model answers. The fp16 graph is broken:
`convert_float_to_float16` leaves a Cast node emitting float16 where the graph
expects float, and onnxruntime refuses the session. It was not worth fixing.
The exporter also had to be told to write one file. It splits weights into a
`.onnx.data` sidecar by default. This onnxruntime resolves that path against the
process working directory rather than the model. A split graph loads from one
directory only.
## What is still wrong
**Four of the eight destination misses are calendar.** Training cannot move them.
The possessive agenda rules claim those cases at stage 0 and name nothing on
purpose. That caution was free while nothing downstream could name anything
either. It has now cost four points in three separate measurements. The call is
the owner's and it is still open.
**The slot head is exported and not read.** Slots come from the stage-2
extractor. Mapping BIO tags back to text needs character offsets the unigram
tokenizer does not keep, which is its own piece of work.
**`поужинал` is a false clarify**, which is the same defect `thinSingleToken`
was narrowed for on 2026-08-01, arriving now from a different direction.
## On the box
Deployed to homesrv the same day. `voice: routing heads loaded` on start, and
`/trace` shows `routing-heads` winning or thinning every turn. The resident model
and the classifier are both marked never asked. Live probes:
```text
что такое TCP? -> kiwix a real definition
кто такой Линус Торвальдс? -> kiwix a real answer
во сколько я лёг вчера -> personal не нашла у тебя такой записи
вода -> thinned to clarify at 0.233 / 0.983
```
A missing or broken weights file logs and leaves the heads nil, which is
byte-for-byte the cascade that shipped before this.
@@ -0,0 +1,110 @@
# CrisperWhisper 2.0 in Russian, measured
Date: 2026-08-09. Vikunja V-665.
Corpus: `bond005/sberdevices_golos_10h_crowd`, test split, first 200 clips.
Harness: `~/Programs/cw2-eval` on workpc, not in this repo.
Runner: `./.venv/bin/python run_asr.py <arm>...` then `score.py`.
The model card benchmarks disfluency F1 in German and English. It never names
Russian and publishes no per-language WER. So the measurement came before the
wiring.
## The corpus
200 clips, 13.7 minutes, 1001 reference words. Median clip 3.91s, range 1.04s
to 13.5s. Golos crowd is short crowd-sourced Russian spoken close to the
microphone, which is the nearest public thing to someone talking to Maven. The
alternatives are read speech, which flatters every model equally.
Two rows carry a null transcription and are skipped.
Scoring normalizes both sides: lowercase, `ё` to `е`, punctuation stripped, and
digits expanded to Russian words through num2words. Without that last step a
model is penalized for writing `60000` where the reference says
`шестьдесят тысяч`. Thousands separators are joined before expansion, or
`60 000` expands to `шестьдесят ноль`.
## Headline
| arm | WER | CER | exact | empty | RTF |
|---|---|---|---|---|---|
| cw2-turbo-intended | **10.4%** | 3.4% | 65.5% | 0 | 0.065 |
| cw2-turbo-verbatim | 10.8% | **3.1%** | **66.5%** | 0 | 0.065 |
| whisper-turbo | 11.8% | 4.1% | 64.0% | 0 | 0.031 |
| cw2-large-intended | 12.3% | 3.8% | 63.5% | 0 | 0.107 |
| whisper-small | 27.5% | 9.8% | 35.0% | 0 | 0.026 |
`whisper-small` is the floor, because `ggml-small.bin` is what mavsttd loads on
homesrv today. CW2 turbo beats it by 17 points of WER and takes exact matches
from 35.0% to 65.5%.
Two results are worth naming beyond the winner. CW2 turbo beats its own base
model, whisper-large-v3-turbo, by 1.4 points. And it beats CW2 large by 1.9
points, which inverts what the card implies by calling turbo a degraded draft.
No arm returned an empty transcript.
## Intended and verbatim are closer than the mode names suggest
The two modes disagree on 70 of the 200 clips before normalization and on 29
after it. So the raw difference is mostly casing and punctuation, which
normalization removes and which Maven does not read either.
Verbatim scores worse on WER and better on CER and exact matches. The reason is
script, not disfluency:
```text
ref: футбольный матч челси брайтон
int: Футбольный матч Chelsea-Брайтон.
ver: Футбольный матч Челси Брайтон.
```
Intended writes foreign entity names in Latin script and verbatim
transliterates them. Golos references are Cyrillic throughout, so verbatim
collects the exact matches. That is a property of this corpus rather than a
quality difference.
**This corpus cannot settle the mode choice.** Golos crowd is clean short
commands with almost no disfluency. The two modes have nothing to disagree
about here. They separate on spontaneous speech with fillers, restarts and
repairs, which is what the owner speaks. Intended stays the choice for the
reason it was always the choice. Maven wants what was meant, not every stumble
on the way there.
The Latin-script habit is the one finding here that touches routing. The
routing heads were trained on Cyrillic utterances, so an entity name arriving
in Latin script is out of distribution for them. Nothing measures that yet.
## The runtime is workpc, because whisper.cpp cannot load CW2
`num_languages()` in `deps/whisper.cpp/src/whisper.cpp` derives the language
count from the vocabulary size:
```cpp
return n_vocab - 51765 - (is_multilingual() ? 1 : 0);
```
CW2 carries 31 extra tokens, so `n_vocab` is 51897 and this yields 131
languages. The derived `dt` offset becomes 33 and shifts seven special token
ids, including `token_beg` and `token_transcribe`. The architecture is
otherwise byte-identical to whisper-large-v3-turbo, and the new tokens sit
above every whisper special id.
So loading CW2 in whisper.cpp is a patch to a vendored dependency, not a port.
It was not taken, because STT is moving to workpc anyway under V-486. CW2 turbo
becomes the preferred remote and `ggml-small.bin` on homesrv stays the floor,
which is the shape `modelSeam` already uses for routing and replies. The 27.5%
floor is what a turn falls back to when the workstation is down, and this table
is what that costs.
## License
Standard CW2 weights carry `nyra-health-non-commercial-research`. The Pro
variants are commercial-license only. Maven is personal and self-hosted, so the
standard weights are usable and the Pro ones are not free to take.
## What is not measured
Disfluent spontaneous speech, which is the whole reason to prefer Intended.
Long-form audio beyond 13.5s. Far-field or noisy microphones. English, which
Maven also speaks. The ONNX turbo export, which was never run, since the
transformers path already meets the latency budget at RTF 0.065.
+10
View File
@@ -37,6 +37,16 @@ type EmbedderConfig struct {
ModelPath string `json:"model_path,omitempty"`
TokenizerPath string `json:"tokenizer_path,omitempty"`
LibPath string `json:"lib_path,omitempty"`
// HeadsPath — the routing heads graph, which is a fine-tuned COPY of the
// model above with four linear heads on its pooled output (V-664). Empty
// means no heads, and the cascade runs exactly as it did before they
// existed. It shares LibPath and TokenizerPath, and router_heads.json is
// read from the same directory.
//
// It must never be pointed at ModelPath. Memory recall depends on the
// resident copy scoring what it scored, and the fine-tuned one does not.
HeadsPath string `json:"heads_path,omitempty"`
}
// WeatherConfig configures the weather provider for voice queries.
+75
View File
@@ -1,6 +1,7 @@
package config
import (
"net/url"
"strings"
"time"
)
@@ -35,12 +36,54 @@ type WorkstationConfig struct {
// 0 ⇒ DefaultWorkstationTimeout. A big model on a LAN host is slower than
// the resident one, and a request that overruns falls back to the floor.
Timeout Duration `json:"timeout,omitempty"`
// Stt — CrisperWhisper 2.0 on the same machine, a separate service on its
// own port. Absent ⇒ every utterance goes to mavsttd, which is today.
Stt *WorkstationSttConfig `json:"stt,omitempty"`
}
// WorkstationSttConfig — speech-to-text on the workstation.
//
// It is a second service and not a second endpoint on mavgpud: whisper.cpp
// cannot load CrisperWhisper 2.0 at all, because it derives its language count
// from the vocabulary size and CW2's 51897 tokens shift seven special token
// ids. So CW2 runs under transformers, and this block addresses it.
//
// Worth the trouble: CW2 turbo scores 10.4% WER in Russian against 27.5% for
// the ggml-small.bin homesrv loads
// (docs/evals/2026-08-09-crisperwhisper2-russian-wer.md).
type WorkstationSttConfig struct {
// URL — the transcribe endpoint, e.g.
// "http://192.168.1.105:8081/transcribe". Empty ⇒ the block is normalised
// to nil and mavsttd takes every turn.
URL string `json:"url,omitempty"`
// Health — the admission endpoint. Empty ⇒ the URL's origin + "/health".
// It answers 503 while the card is held, and that is the signal.
Health string `json:"health,omitempty"`
// Token — the bearer token the service checks. Audio is the most sensitive
// thing that crosses this seam, so a LAN deployment should set one. Write
// it as ${MAVEN_STT_TOKEN} and keep the value in deploy/telegram.env, the
// way every other secret in this file is written.
Token string `json:"token,omitempty"`
// Probe — how often admission is re-checked. 0 ⇒ DefaultWorkstationProbe.
Probe Duration `json:"probe,omitempty"`
// Timeout — the per-request budget for one utterance. 0 ⇒
// DefaultWorkstationSttTimeout. A request that overruns falls back to
// mavsttd, which costs a worse transcript and not the turn.
Timeout Duration `json:"timeout,omitempty"`
}
// Workstation defaults, applied in normaliseWorkstation.
const (
DefaultWorkstationProbe = 15 * time.Second
DefaultWorkstationTimeout = 90 * time.Second
// One utterance, not one completion. A voice turn waits on this, so the
// budget is a few seconds and not a minute and a half.
DefaultWorkstationSttTimeout = 10 * time.Second
)
// normaliseWorkstation applies the block's defaults. No address, no preferred
@@ -63,4 +106,36 @@ func (c *Config) normaliseWorkstation() {
if w.Timeout <= 0 {
w.Timeout = Duration(DefaultWorkstationTimeout)
}
normaliseWorkstationStt(w)
}
// normaliseWorkstationStt applies the speech-to-text block's defaults. No
// address, no remote: mavsttd then takes every utterance, which is today.
func normaliseWorkstationStt(w *WorkstationConfig) {
if w.Stt != nil && strings.TrimSpace(w.Stt.URL) == "" {
w.Stt = nil
}
if w.Stt == nil {
return
}
s := w.Stt
if strings.TrimSpace(s.Health) == "" {
s.Health = healthOrigin(s.URL)
}
if s.Probe <= 0 {
s.Probe = Duration(DefaultWorkstationProbe)
}
if s.Timeout <= 0 {
s.Timeout = Duration(DefaultWorkstationSttTimeout)
}
}
// healthOrigin derives the admission endpoint from the transcribe endpoint.
// The URL names a path, so appending to it would ask for /transcribe/health.
func healthOrigin(raw string) string {
u, err := url.Parse(raw)
if err != nil || u.Host == "" {
return strings.TrimRight(raw, "/") + "/health"
}
return u.Scheme + "://" + u.Host + "/health"
}
+6 -3
View File
@@ -14,12 +14,15 @@ import (
"github.com/kami/maven/internal/decision"
)
// The two routing engines, named as claimants. They are one stage and not two,
// because only one of them ever runs: the classifier is reached when the model
// is absent or errored, never alongside it.
// The three routing engines, named as claimants. The model and the classifier
// are one stage and not two, because only one of them ever runs: the classifier
// is reached when the model is absent or errored, never alongside it. The heads
// run before both and decline on low confidence, so they can appear beside
// either one in a record.
const (
claimantLLM = "llm-router"
claimantClassifier = "classifier"
claimantHeads = "routing-heads"
)
// thinReason names which arm of gateLLMDecision cut the confidence. The gate
+12 -2
View File
@@ -1,10 +1,13 @@
package router
import "testing"
import (
"strings"
"testing"
)
func TestEmbedderIDFromModelPath(t *testing.T) {
got := modelIDFromPath("/opt/maven/models/embedder/multilingual-e5-small.onnx")
if got != "multilingual-e5-small@384" {
if got != "multilingual-e5-small@384/tok2" {
t.Fatalf("modelIDFromPath = %q", got)
}
// A different model file must produce a different id, even at 384 dim.
@@ -12,6 +15,13 @@ func TestEmbedderIDFromModelPath(t *testing.T) {
if old == got {
t.Fatal("two different models share one id")
}
// The tokenizer is half of what makes a vector, and it changes under a
// model file whose name never moves (V-664). An id that ignored it would
// leave stored passages in one space and every new query in another, with
// nothing to trigger the re-embed.
if !strings.Contains(got, "/tok") {
t.Fatalf("id %q does not name the tokenizer revision", got)
}
}
func TestEmbedderIDIncludesDim(t *testing.T) {
+86
View File
@@ -0,0 +1,86 @@
package eval
import (
"context"
"os"
"path/filepath"
"testing"
"github.com/kami/maven/internal/config"
"github.com/kami/maven/internal/router"
)
// TestONNXRoutingHeads — the cascade with the routing heads wired, which is
// what V-664 deploys. Opt-in via MAVEN_ONNX_LIB, same as TestONNXBaseline, and
// one TestONNX* per process.
//
// The comparison worth reading is against TestONNXBaseline, which is the same
// cascade with the same grammars and the same classifier floor and no heads.
// Only the middle arm varies.
//
// It also checks the Go unigram tokenizer against the Python one, because 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.
func TestONNXRoutingHeads(t *testing.T) {
lib := os.Getenv("MAVEN_ONNX_LIB")
if lib == "" {
t.Skip("MAVEN_ONNX_LIB unset — see AGENTS.md § Embedder model for intent routing")
}
// Absolute, because onnxruntime resolves a graph's external weights file
// against the model path it was given, and a relative one lands in the
// test's working directory.
root, err := filepath.Abs("../../..")
if err != nil {
t.Fatal(err)
}
model := filepath.Join(root, "models/embedder/multilingual-e5-small/model_quantized.onnx")
tok := filepath.Join(root, "models/embedder/multilingual-e5-small/tokenizer.json")
heads := filepath.Join(root, "models/embedder/router-heads/router_heads.onnx")
for _, p := range []string{lib, model, tok, heads} {
if _, err := os.Stat(p); err != nil {
t.Skipf("missing %s: %v", p, err)
}
}
emb, err2 := router.NewONNXEmbedder(model, tok, lib)
if err2 != nil {
t.Skipf("onnx embedder unavailable: %v", err2)
}
err = nil
defer emb.Close()
h, err := router.NewRouterHeads(heads, tok)
if err != nil {
t.Skipf("routing heads unavailable: %v", err)
}
defer h.Close()
f, err := Load()
if err != nil {
t.Fatalf("Load: %v", err)
}
rep, err := Score(context.Background(), "heads+classifier", withHeads(t, emb, h), f)
if err != nil {
t.Fatalf("Score: %v", err)
}
t.Log("\n" + rep.String() + rep.Failures())
}
// withHeads mirrors newBaselineRouter and adds the one arm under test. It is a
// separate function rather than a parameter so the baseline's signature stays
// the shape every other test calls it with.
func withHeads(t *testing.T, emb router.Embedder, h *router.RouterHeads) *router.Router {
t.Helper()
acts := router.DefaultActMatcher{Fns: actFns}
return router.New(router.Config{
Grammars: baselineGrammars(acts),
Classifier: newBaselineClassifier(t, emb),
Extractor: router.Extractor{
Time: router.StubDateTimeParser{},
Acts: acts,
Facts: router.DefaultFactParser{},
},
Threshold: config.DefaultRouterThreshold,
Heads: h,
})
}
+243
View File
@@ -0,0 +1,243 @@
package router
import (
"context"
"encoding/json"
"fmt"
"math"
"os"
"path/filepath"
ort "github.com/yalue/onnxruntime_go"
)
// The routing heads (V-546, V-661, V-664). Four linear heads over one masked
// mean pool of a fine-tuned copy of multilingual-e5-small: intent,
// destination, BIO slot tags and clarify. Trained on workpc, exported to ONNX,
// and read here.
//
// Why this is not the classifier. The classifier compares one utterance to
// frozen seed phrases by cosine. A head is a softmax over the label set, so it
// cannot name a value that does not exist, and its max is a calibratable
// confidence where Confidence: 1.0 was a hardcode.
//
// Why it is not the resident model either. It answers in single-digit
// milliseconds against the model's p50 of 1.19s, and it names a destination
// the classifier arm never names at all.
//
// The body is a COPY of the embedder weights, fine-tuned. It must never
// replace models/embedder/multilingual-e5-small — memory recall depends on
// that file scoring what it scored.
//
// The slot head is exported and deliberately not read. Slots already come from
// the stage-2 extractor, and mapping BIO tags back to text needs character
// offsets the unigram tokenizer does not keep. Reading it is separate work.
const (
// headsSeq — the sequence length the heads were trained at. Padding is
// masked out of both attention and the pool, so this changes nothing but
// truncation, and truncation is what training did at 64.
headsSeq = 64
// headsThreshold — max softmax over the intent head, below which the heads
// decline and the cascade carries on to the resident model.
//
// 0.6 is the knee measured on the 88-case intent fixture
// (docs/evals/2026-08-08-routing-heads-in-go.md). It keeps 81 of 88 cases
// at 97.5% accuracy. Every higher value up to 0.9 drops right answers and
// keeps the same two wrong ones, so it buys nothing.
headsThreshold = 0.6
)
// RouterHeads runs the exported graph. Nil is a working value everywhere: a
// deployment with no weights file routes exactly as it did before this
// existed.
type RouterHeads struct {
tokenizer *unigramTokenizer
session *ort.DynamicSession[int64, float32]
intents []Intent
sources []Source
threshold float64
}
// headsMeta — router_heads.json, written beside the weights by the exporter.
// The label order is the head's output order and cannot be inferred from Go.
type headsMeta struct {
Intents []string `json:"intents"`
Sources []string `json:"sources"`
Prefix string `json:"prefix"`
}
// NewRouterHeads loads the graph and its label order. modelPath points at the
// .onnx; the external weights and router_heads.json sit beside it.
//
// It assumes the ONNX environment is already initialised, because the embedder
// does that at startup and the runtime allows it once.
func NewRouterHeads(modelPath, tokenizerPath string) (*RouterHeads, error) {
metaPath := filepath.Join(filepath.Dir(modelPath), "router_heads.json")
raw, err := os.ReadFile(metaPath)
if err != nil {
return nil, fmt.Errorf("heads: read %s: %w", metaPath, err)
}
var meta headsMeta
if err := json.Unmarshal(raw, &meta); err != nil {
return nil, fmt.Errorf("heads: parse %s: %w", metaPath, err)
}
if meta.Prefix != queryPrefix {
return nil, fmt.Errorf("heads: trained with prefix %q, this build uses %q",
meta.Prefix, queryPrefix)
}
intents := make([]Intent, len(meta.Intents))
for i, s := range meta.Intents {
intents[i] = Intent(s)
}
sources := make([]Source, len(meta.Sources))
for i, s := range meta.Sources {
// SourceUnknown is not in Sources, because it is the absence of a
// choice. It is a class the head can emit, and the one it should emit
// often, so it is allowed here and nowhere else.
if s != string(SourceUnknown) && !ValidSource(Source(s)) {
return nil, fmt.Errorf("heads: unknown destination %q in %s", s, metaPath)
}
sources[i] = Source(s)
}
tok, err := newUnigramTokenizer(tokenizerPath)
if err != nil {
return nil, fmt.Errorf("heads: tokenizer: %w", err)
}
session, err := ort.NewDynamicSession[int64, float32](
modelPath,
[]string{"input_ids", "attention_mask"},
[]string{"intent", "source", "slots", "clarify"},
)
if err != nil {
return nil, fmt.Errorf("heads: create session: %w", err)
}
return &RouterHeads{
tokenizer: tok,
session: session,
intents: intents,
sources: sources,
threshold: headsThreshold,
}, nil
}
func (h *RouterHeads) Close() error {
if h == nil {
return nil
}
h.session.Destroy()
return nil
}
// headsResult — one forward pass, read back.
type headsResult struct {
Intent Intent
Source Source
Confidence float64
Clarify bool
}
// Route runs the heads and reports whether they are confident enough to answer.
// A false second return is a decline, not an error: the cascade goes on to the
// resident model, which is what happens today.
func (h *RouterHeads) Route(ctx context.Context, utterance string) (headsResult, bool, error) {
if h == nil {
return headsResult{}, false, nil
}
ids, mask, _ := h.tokenizer.Encode(queryPrefix + utterance)
ids, mask = ids[:headsSeq], mask[:headsSeq]
// The tokenizer pads and truncates to its own length, which is longer than
// this one. Cutting the tail can cut the separator with it, so put it back.
if mask[headsSeq-1] == 1 {
ids[headsSeq-1] = sepTokenID
}
shape := ort.NewShape(1, headsSeq)
idsT, err := ort.NewTensor(shape, ids)
if err != nil {
return headsResult{}, false, fmt.Errorf("heads: ids tensor: %w", err)
}
defer idsT.Destroy()
maskT, err := ort.NewTensor(shape, mask)
if err != nil {
return headsResult{}, false, fmt.Errorf("heads: mask tensor: %w", err)
}
defer maskT.Destroy()
intentT, err := ort.NewEmptyTensor[float32](ort.NewShape(1, int64(len(h.intents))))
if err != nil {
return headsResult{}, false, fmt.Errorf("heads: intent tensor: %w", err)
}
defer intentT.Destroy()
sourceT, err := ort.NewEmptyTensor[float32](ort.NewShape(1, int64(len(h.sources))))
if err != nil {
return headsResult{}, false, fmt.Errorf("heads: source tensor: %w", err)
}
defer sourceT.Destroy()
slotsT, err := ort.NewEmptyTensor[float32](ort.NewShape(1, headsSeq, int64(numBIOTags)))
if err != nil {
return headsResult{}, false, fmt.Errorf("heads: slots tensor: %w", err)
}
defer slotsT.Destroy()
clarifyT, err := ort.NewEmptyTensor[float32](ort.NewShape(1, 2))
if err != nil {
return headsResult{}, false, fmt.Errorf("heads: clarify tensor: %w", err)
}
defer clarifyT.Destroy()
if err := h.session.Run(
[]*ort.Tensor[int64]{idsT, maskT},
[]*ort.Tensor[float32]{intentT, sourceT, slotsT, clarifyT},
); err != nil {
return headsResult{}, false, fmt.Errorf("heads: run: %w", err)
}
// The graph applies its own softmax, so these are probabilities and the max
// is the same number the eval calibrated the threshold against.
i, conf := argmax(intentT.GetData())
res := headsResult{
Intent: h.intents[i],
Confidence: conf,
}
cl := clarifyT.GetData()
res.Clarify = len(cl) == 2 && cl[1] > cl[0]
// The destination head is trained on query rows and is meaningless on any
// other intent, the same way queryWalk is never reached by one.
if res.Intent == IntentQuery {
s, _ := argmax(sourceT.GetData())
res.Source = h.sources[s]
}
// The clarify head decides on its own, and it decides first. It answers a
// different question from the intent head — not which intent, but whether
// there is enough here to act on at all — so a low intent confidence is no
// reason to discard it. It is usually the same turns: "вода" reads as
// intent act at 0.23 and clarify at 0.98, and letting the intent threshold
// bury that hands the turn to the classifier, which routes it confidently
// and never asks.
if res.Clarify {
return res, true, nil
}
if conf < h.threshold {
return res, false, nil
}
return res, true, nil
}
// numBIOTags — O plus B- and I- for each of Maven's five slots. The head is not
// read, but the graph writes it and the output tensor has to be the right size.
const numBIOTags = 11
func argmax(v []float32) (int, float64) {
best, bestV := 0, math.Inf(-1)
for i, x := range v {
if float64(x) > bestV {
best, bestV = i, float64(x)
}
}
return best, bestV
}
+18 -8
View File
@@ -66,12 +66,19 @@ func NewONNXEmbedder(modelPath, tokenizerPath, libPath string) (*onnxEmbedder, e
func (e *onnxEmbedder) Dim() int { return embedDim }
// ID names the loaded model for the DB marker (Vikunja #378): the model file's
// own name plus the dimension, so pointing the config at another model changes
// the string on its own.
// own name, the dimension, and the tokenizer revision, so pointing the config
// at another model changes the string on its own.
func (e *onnxEmbedder) ID() string { return e.id }
// tokenizerRev — bumped whenever the tokenizer changes what it emits for the
// same text, because that changes every vector while the model file's name
// stays put. Rev 2 is the fix for the reversed word pieces (V-664): stored
// passages embedded under rev 1 no longer sit in the same space as a query
// embedded now, and ReembedAll rewrites them because this string moved.
const tokenizerRev = 2
// modelIDFromPath turns /opt/.../multilingual-e5-small.onnx into
// "multilingual-e5-small@384".
// "multilingual-e5-small@384/tok2".
func modelIDFromPath(modelPath string) string {
name := modelPath
if i := strings.LastIndexAny(name, "/\\"); i >= 0 {
@@ -81,7 +88,7 @@ func modelIDFromPath(modelPath string) string {
if name == "" {
name = "onnx"
}
return fmt.Sprintf("%s@%d", name, embedDim)
return fmt.Sprintf("%s@%d/tok%d", name, embedDim, tokenizerRev)
}
// Embed treats the text as a query. The classifier compares one short
@@ -339,14 +346,17 @@ func (t *unigramTokenizer) encodeWord(word string) []int64 {
}
}
// Backtracking walks the word from its end, and prepending each piece puts
// it back in reading order. There used to be a second reverse after this
// loop, which undid it: every multi-piece word came out backwards, and
// "query: вода" tokenized to [0 12 1294 41 12489 2] where the reference
// tokenizer gives [0 41 1294 12 12489 2] (V-664). A transformer reads
// position, so the pieces of a long Russian word were being read in the
// wrong order on every turn.
var result []int64
for i := n; i > 0; i = prev[i] {
result = append([]int64{bestID[i]}, result...)
}
// Reverse
for l, r := 0, len(result)-1; l < r; l, r = l+1, r-1 {
result[l], result[r] = result[r], result[l]
}
return result
}
+62
View File
@@ -31,6 +31,12 @@ type Config struct {
// error/parse failure, falls through to the classifier (never fails the
// turn on the model).
LLM *LLMRouter
// Heads — optional routing heads over the fine-tuned embedder copy. When
// set, Route consults them after stage 0 and before the LLM router. They
// decline below their own confidence threshold, so a low-confidence turn
// reaches the model exactly as it does today. Nil is the shipped-before
// behaviour and costs nothing.
Heads *RouterHeads
}
// Router — the deterministic cascade. Route never guesses: stage 0 wins
@@ -42,6 +48,7 @@ type Router struct {
extractor Extractor
threshold float64
llm *LLMRouter
heads *RouterHeads
}
func New(cfg Config) *Router {
@@ -51,6 +58,7 @@ func New(cfg Config) *Router {
extractor: cfg.Extractor,
threshold: cfg.Threshold,
llm: cfg.LLM,
heads: cfg.Heads,
}
}
@@ -98,6 +106,60 @@ func (r *Router) Route(ctx context.Context, utterance string, now time.Time) (De
}
r.noteGrammarOutcomes(ctx, len(r.grammars), declinedBuild, "", "")
// stage 0b — routing heads (when wired). A softmax over the label set, so
// it cannot name an intent or a destination that does not exist, and its
// max is a real confidence. It runs before the model because it is three
// orders of magnitude faster and scores better on both halves of the route.
//
// It declines below its threshold rather than clarifying. A declined turn
// carries on to the model and then the classifier, which is what a box with
// no weights file does on every turn.
if r.heads != nil {
res, ok, err := r.heads.Route(ctx, utterance)
switch {
case err != nil:
log.Printf("router: heads fell through to the rest of the cascade: %v", err)
decision.Note(ctx, decision.Claim{
Stage: decision.StageRoute, Claimant: claimantHeads,
Outcome: decision.Declined, Reason: "error: " + err.Error(),
})
case !ok:
decision.Note(ctx, decision.Scored(decision.StageRoute, claimantHeads,
string(res.Intent), res.Confidence, decision.Declined,
"below the heads confidence threshold"))
default:
d := Decision{
Utterance: utterance,
Stage: 2,
Intent: res.Intent,
Confidence: res.Confidence,
Source: res.Source,
Clarify: res.Clarify,
}
r.fillSlots(ctx, &d, now)
decision.Note(ctx, decision.Claim{
Stage: decision.StageRoute, Claimant: claimantLLM,
Outcome: decision.NeverAsked, Reason: "the routing heads answered",
})
decision.Note(ctx, decision.Claim{
Stage: decision.StageRoute, Claimant: claimantClassifier,
Outcome: decision.NeverAsked, Reason: "the routing heads answered",
})
outcome, reason := decision.Won, ""
if d.Clarify {
outcome, reason = decision.Thinned, "the clarify head says there is too little here to act on"
}
decision.Note(ctx, decision.Scored(decision.StageRoute, claimantHeads,
string(d.Intent), d.Confidence, outcome, reason))
return d, nil
}
} else {
decision.Note(ctx, decision.Claim{
Stage: decision.StageRoute, Claimant: claimantHeads,
Outcome: decision.NeverAsked, Reason: "no routing heads are wired",
})
}
// stage 1a — LLM router (when wired). It reasons over the utterance instead
// of nearest-centroid guessing. On any error/parse-fail, fall through to the
// classifier cascade (never fail the turn on the model).
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package stt
import (
"bytes"
"context"
"encoding/json"
"errors"
"fmt"
"net/http"
"strconv"
"time"
"github.com/kami/maven/internal/audio"
)
// HTTPTranscriber — speech-to-text on another host, over HTTP.
//
// mavsttd is whisper.cpp linked into a Go daemon and reached over a unix
// socket. CrisperWhisper 2.0 cannot be reached that way: whisper.cpp derives
// its language count from the vocabulary size, and CW2's 51897 tokens shift
// seven special token ids. It runs under transformers instead, as a service
// beside the model on workpc. See docs/evals/2026-08-09-crisperwhisper2-russian-wer.md.
//
// So this is the second transport for the same seam, not a second seam. The
// caller still sees stt.Transcriber and one method.
type HTTPTranscriber struct {
url string
token string
lang string
http *http.Client
}
// NewHTTPTranscriber builds the remote client. token may be empty for a
// service on a trusted socket, but audio is the most sensitive thing that
// crosses this seam, so a LAN deployment should always set one.
func NewHTTPTranscriber(url, token, lang string, timeout time.Duration) *HTTPTranscriber {
return &HTTPTranscriber{
url: url,
token: token,
lang: lang,
http: &http.Client{Timeout: timeout},
}
}
// ErrFormat — the audio is not the one canonical shape. Refused at the seam
// rather than sent to a model that expects something else.
var ErrFormat = errors.New("stt: audio is not 16kHz mono pcm_s16le")
type httpTranscript struct {
Text string `json:"text"`
Confidence float64 `json:"confidence"`
}
// Transcribe posts the raw PCM and reads back the text.
//
// The body is the PCM bytes themselves rather than JSON. A minute of 16kHz
// mono is under 2MB raw and about 2.6MB base64, and the format is fixed by
// audio.PCM16kMono, so a header carries it more cheaply than an envelope.
func (t *HTTPTranscriber) Transcribe(ctx context.Context, a audio.Audio) (string, float64, error) {
if !a.Format.IsValid() {
return "", 0, ErrFormat
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, t.url, bytes.NewReader(a.Bytes))
if err != nil {
return "", 0, fmt.Errorf("stt: build request: %w", err)
}
req.Header.Set("Content-Type", "application/octet-stream")
req.Header.Set("X-Sample-Rate", strconv.Itoa(a.Format.SampleRate))
req.Header.Set("X-Channels", strconv.Itoa(a.Format.Channels))
req.Header.Set("X-Sample-Bits", strconv.Itoa(a.Format.SampleBits))
req.Header.Set("X-Language", t.lang)
if t.token != "" {
req.Header.Set("Authorization", "Bearer "+t.token)
}
resp, err := t.http.Do(req)
if err != nil {
return "", 0, fmt.Errorf("stt: post audio: %w", err)
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return "", 0, fmt.Errorf("stt: remote returned %d", resp.StatusCode)
}
var out httpTranscript
if err := json.NewDecoder(resp.Body).Decode(&out); err != nil {
return "", 0, fmt.Errorf("stt: decode transcript: %w", err)
}
return out.Text, out.Confidence, nil
}
var _ Transcriber = (*HTTPTranscriber)(nil)
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package stt
import (
"context"
"errors"
"io"
"net/http"
"net/http/httptest"
"strconv"
"testing"
"time"
"github.com/kami/maven/internal/audio"
)
func TestHTTPTranscriberSendsRawPCM(t *testing.T) {
t.Parallel()
var gotBody []byte
var gotHeader http.Header
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
gotBody, _ = io.ReadAll(r.Body)
gotHeader = r.Header.Clone()
w.Header().Set("Content-Type", "application/json")
_, _ = io.WriteString(w, `{"text":"привет","confidence":0.82}`)
}))
defer srv.Close()
a := audio.Audio{Format: audio.PCM16kMono, Bytes: []byte("pcm-bytes")}
tr := NewHTTPTranscriber(srv.URL, "s3cret", "ru", 2*time.Second)
text, conf, err := tr.Transcribe(context.Background(), a)
if err != nil {
t.Fatalf("Transcribe: %v", err)
}
if text != "привет" || conf != 0.82 {
t.Fatalf("got %q %v", text, conf)
}
if string(gotBody) != "pcm-bytes" {
t.Fatalf("body should be the PCM itself, got %q", gotBody)
}
if got := gotHeader.Get("X-Sample-Rate"); got != strconv.Itoa(audio.PCM16kMono.SampleRate) {
t.Fatalf("X-Sample-Rate = %q", got)
}
if got := gotHeader.Get("X-Language"); got != "ru" {
t.Fatalf("X-Language = %q", got)
}
// Audio is the most sensitive thing crossing this seam.
if got := gotHeader.Get("Authorization"); got != "Bearer s3cret" {
t.Fatalf("Authorization = %q", got)
}
}
func TestHTTPTranscriberOmitsEmptyToken(t *testing.T) {
t.Parallel()
var auth string
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
auth = r.Header.Get("Authorization")
_, _ = io.WriteString(w, `{"text":"x"}`)
}))
defer srv.Close()
a := audio.Audio{Format: audio.PCM16kMono, Bytes: []byte("x")}
if _, _, err := NewHTTPTranscriber(srv.URL, "", "ru", time.Second).Transcribe(context.Background(), a); err != nil {
t.Fatalf("Transcribe: %v", err)
}
if auth != "" {
t.Fatalf("Authorization should be absent, got %q", auth)
}
}
func TestHTTPTranscriberRefusesWrongFormat(t *testing.T) {
t.Parallel()
a := audio.Audio{Format: audio.Format{SampleRate: 44100, Channels: 2, SampleBits: 16, Encoding: "pcm_s16le"}}
_, _, err := NewHTTPTranscriber("http://example.invalid", "", "ru", time.Second).Transcribe(context.Background(), a)
if !errors.Is(err, ErrFormat) {
t.Fatalf("want ErrFormat, got %v", err)
}
}
func TestHTTPTranscriberErrorsOnBadStatus(t *testing.T) {
t.Parallel()
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
w.WriteHeader(http.StatusUnauthorized)
}))
defer srv.Close()
a := audio.Audio{Format: audio.PCM16kMono, Bytes: []byte("x")}
_, _, err := NewHTTPTranscriber(srv.URL, "", "ru", time.Second).Transcribe(context.Background(), a)
if err == nil {
t.Fatal("a 401 must be an error, so the Pair falls back")
}
}
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package stt
import (
"context"
"errors"
"log"
"net/http"
"sync"
"sync/atomic"
"time"
"github.com/kami/maven/internal/audio"
)
// Pair — a preferred transcriber on the workstation, with mavsttd as the floor.
//
// Same arrangement as llm.Pair and for the same reason. The microphone is at
// workpc, the card there has 16GB, and CrisperWhisper 2.0 turbo scores 10.4%
// WER in Russian against 27.5% for the ggml-small.bin homesrv loads
// (docs/evals/2026-08-09-crisperwhisper2-russian-wer.md). The workstation is
// never assumed up: it sleeps, and the card is often held by a training run.
//
// Speech-to-text has only the silent half of the degradation rule. A worse
// transcript is still a turn, and there is nothing to name a gap about, so
// Transcribe always falls back. That is the whole difference from llm.Pair,
// which also carries CompleteRemote for callers that must refuse instead.
type Pair struct {
remote Transcriber
floor Transcriber
// up — the cached admission answer, written only by the prober and read by
// every turn. A voice turn must never wait on a machine that may be asleep.
up atomic.Bool
health string
interval time.Duration
http *http.Client
stop chan struct{}
stopOnce sync.Once
}
const (
probeTimeout = 2 * time.Second
defaultProbeInterval = 15 * time.Second
)
// ErrNoFloor — a Pair was built with no local transcriber to fall back to. A
// configuration mistake: the floor is what makes the remote optional.
var ErrNoFloor = errors.New("stt: no floor transcriber")
// NewPair builds the two-transcriber arrangement. remote may be nil, which is
// the unconfigured deploy: every turn goes to the floor and nothing probes.
func NewPair(remote, floor Transcriber, health string, interval time.Duration) *Pair {
if interval <= 0 {
// The config normalises this, so a zero here is a caller that built the
// Pair directly. Panicking in a ticker is the wrong way to say so.
interval = defaultProbeInterval
}
return &Pair{
remote: remote,
floor: floor,
health: health,
interval: interval,
http: &http.Client{Timeout: probeTimeout},
stop: make(chan struct{}),
}
}
// Start begins probing. The first probe runs before the first tick, so a
// workstation that is already up serves the first utterance rather than the
// second. Safe with a nil remote.
func (p *Pair) Start(ctx context.Context) {
if p.remote == nil || p.health == "" {
return
}
go func() {
p.probe(ctx)
t := time.NewTicker(p.interval)
defer t.Stop()
for {
select {
case <-ctx.Done():
return
case <-p.stop:
return
case <-t.C:
p.probe(ctx)
}
}
}()
}
// Stop ends the prober. Idempotent and safe from two goroutines.
func (p *Pair) Stop() {
p.stopOnce.Do(func() { close(p.stop) })
}
// Available reports whether the workstation will transcribe right now.
func (p *Pair) Available() bool {
return p.remote != nil && p.up.Load()
}
func (p *Pair) probe(ctx context.Context) {
ctx, cancel := context.WithTimeout(ctx, probeTimeout)
defer cancel()
req, err := http.NewRequestWithContext(ctx, http.MethodGet, p.health, nil)
if err != nil {
p.set(false)
return
}
resp, err := p.http.Do(req)
if err != nil {
p.set(false)
return
}
defer resp.Body.Close()
p.set(resp.StatusCode == http.StatusOK)
}
// set records the admission answer and logs only transitions. A machine that
// sleeps nightly would otherwise write one line per interval forever.
func (p *Pair) set(up bool) {
if p.up.Swap(up) == up {
return
}
if up {
log.Printf("stt: workstation transcriber available at %s", p.health)
} else {
log.Print("stt: workstation transcriber unavailable, falling back to mavsttd")
}
}
// Transcribe sends the audio to the workstation when it will take work, and to
// mavsttd otherwise. A remote that fails mid-request falls back too, because
// the admission answer is a cache and can be one interval out of date.
//
// Killing the remote mid-session must not drop the turn. That is the whole
// point of the floor, and it is what TestPairFallsBackWhenRemoteFails pins.
func (p *Pair) Transcribe(ctx context.Context, a audio.Audio) (string, float64, error) {
if p.floor == nil {
return "", 0, ErrNoFloor
}
if p.Available() {
text, conf, err := p.remote.Transcribe(ctx, a)
if err == nil {
log.Print("stt: transcribed on the workstation")
return text, conf, nil
}
// The cached answer was wrong. Correct it now rather than sending the
// next utterance into the same hole, then fall back.
p.set(false)
log.Printf("stt: workstation failed mid-request, falling back: %v", err)
}
return p.floor.Transcribe(ctx, a)
}
var _ Transcriber = (*Pair)(nil)
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package stt
import (
"context"
"errors"
"net/http"
"net/http/httptest"
"sync/atomic"
"testing"
"time"
"github.com/kami/maven/internal/audio"
)
// scripted — a Transcriber that answers with a fixed text, or fails.
type scripted struct {
text string
err error
calls atomic.Int32
}
func (s *scripted) Transcribe(_ context.Context, _ audio.Audio) (string, float64, error) {
s.calls.Add(1)
if s.err != nil {
return "", 0, s.err
}
return s.text, 0.9, nil
}
func sample() audio.Audio {
return audio.Audio{Format: audio.PCM16kMono, Bytes: make([]byte, 3200)}
}
// up builds a Pair whose admission answer is already true, without probing.
func up(remote, floor Transcriber) *Pair {
p := NewPair(remote, floor, "", time.Minute)
p.up.Store(true)
return p
}
func TestPairPrefersTheWorkstation(t *testing.T) {
t.Parallel()
remote := &scripted{text: "с рабочей станции"}
floor := &scripted{text: "с homesrv"}
text, _, err := up(remote, floor).Transcribe(context.Background(), sample())
if err != nil {
t.Fatalf("Transcribe: %v", err)
}
if text != "с рабочей станции" {
t.Fatalf("want the remote transcript, got %q", text)
}
if floor.calls.Load() != 0 {
t.Fatalf("floor was called %d times, want 0", floor.calls.Load())
}
}
// The turn is what matters. A remote that dies mid-session must cost a worse
// transcript and nothing else. This is the V-486 bar.
func TestPairFallsBackWhenRemoteFails(t *testing.T) {
t.Parallel()
remote := &scripted{err: errors.New("connection refused")}
floor := &scripted{text: "с homesrv"}
p := up(remote, floor)
text, conf, err := p.Transcribe(context.Background(), sample())
if err != nil {
t.Fatalf("a failed remote must not fail the turn: %v", err)
}
if text != "с homesrv" {
t.Fatalf("want the floor transcript, got %q", text)
}
if conf != 0.9 {
t.Fatalf("want the floor confidence, got %v", conf)
}
if p.Available() {
t.Fatal("a failed request must correct the cached admission answer")
}
// The next utterance goes straight to the floor rather than into the
// same hole.
if _, _, err := p.Transcribe(context.Background(), sample()); err != nil {
t.Fatalf("second turn: %v", err)
}
if remote.calls.Load() != 1 {
t.Fatalf("remote called %d times, want 1", remote.calls.Load())
}
}
func TestPairWithNoRemoteIsTheFloor(t *testing.T) {
t.Parallel()
floor := &scripted{text: "с homesrv"}
p := NewPair(nil, floor, "", time.Minute)
p.Start(context.Background()) // no health url, so this is a no-op
if p.Available() {
t.Fatal("an unconfigured remote is never available")
}
text, _, err := p.Transcribe(context.Background(), sample())
if err != nil {
t.Fatalf("Transcribe: %v", err)
}
if text != "с homesrv" {
t.Fatalf("want the floor transcript, got %q", text)
}
}
func TestPairWithNoFloorRefuses(t *testing.T) {
t.Parallel()
_, _, err := NewPair(nil, nil, "", time.Minute).Transcribe(context.Background(), sample())
if !errors.Is(err, ErrNoFloor) {
t.Fatalf("want ErrNoFloor, got %v", err)
}
}
func TestPairProbeReadsHealth(t *testing.T) {
t.Parallel()
var ok atomic.Bool
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
if !ok.Load() {
w.WriteHeader(http.StatusServiceUnavailable)
return
}
w.WriteHeader(http.StatusOK)
}))
defer srv.Close()
p := NewPair(&scripted{text: "remote"}, &scripted{text: "floor"}, srv.URL, time.Minute)
p.probe(context.Background())
if p.Available() {
t.Fatal("a 503 means the card is busy, so the workstation is not available")
}
ok.Store(true)
p.probe(context.Background())
if !p.Available() {
t.Fatal("a 200 means the workstation will take work")
}
}
func TestPairStopIsIdempotent(t *testing.T) {
t.Parallel()
p := NewPair(nil, &scripted{}, "", time.Minute)
p.Stop()
p.Stop()
}