Maven/CLAUDE.md

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Maven is a self-hosted, privacy-first voice assistant (Russian + English). Go daemons talking over unix sockets; one resident small model for routing + phrasing; whisper.cpp STT, piper TTS. Deploy target is a Ryzen laptop (homesrv) with Vulkan offload to the Vega iGPU (n_gpu_layers: 99, compose passes /dev/dri + the render gid) — the resident model stays ≤1.7B either way.

Resident model: currently Qwen3-1.7B (UD-Q4_K_XL), stock — not yet the CPT'd one. It replaced Qwen3.5-0.8B on 2026-07-31 because it measured better on both fixtures we have: 67.5% vs 59.7% intent-only on the 77-case RU routing fixture, and 20/27 vs 11-17/27 on the talk fixture. See MODEL-BAKEOFF-31-07-2026.md. It is a Thinking variant, so n_ctx is 4096 — reasoning tokens need the room, and 4096 is what the scores above were measured at.

The target is still the locally CPT'd Qwen3-1.7B (Vikunja #122, training in flight). Stock already speaks good Russian; what it gets wrong is the persona — it writes я рад, masculine, where Maven needs рада. That is what the CPT is for.

Do not bother with sub-500M models. LFM2.5-230M and 350M were measured on 2026-07-31 and both are unusable in Russian: the 350M routes at 5.2% (worse than guessing) and answers "столица Франции?" with the invented non-word "Сторзит"; the 230M replies to Russian in Spanish. Their strong published IFEval/BFCL numbers are English-only. Model files live in /mnt/hdd1/llms, bind-mounted to /opt/maven/models/llm — which shadows the repo's models/llm/, so the LFM2.5 gguf sitting there is not loaded by anything. Swapping the resident model is a one-line change to phraser.model_path in deploy/mavend.json.

See REARCH.md for the target architecture, DESIGN.md for the folded design spec, and AGENTS.md for local-preview + model-download recipes.

Build & test

CGO daemons (mavend, mavsttd, mavttsd, mavenclient) need the vendored toolchain and libs wired through the Makefile — do not call go build on them bare, use make:

make build          # all 9 binaries
make build-web      # single daemon (pure-Go ones: web/waked/poll/caldav build without CGO)
make test           # go test -race across ./internal/... ./cmd/... with CGO env set

Run a single test (must carry the CGO env for packages that touch STT/TTS/voice):

CGO_CFLAGS="-I$(pwd)/deps/include -I$(pwd)/deps/whisper.cpp/ggml/include" \
CGO_LDFLAGS="-L$(pwd)/deps/lib -Wl,-rpath,$(pwd)/deps/lib" \
LD_LIBRARY_PATH="$(pwd)/deps/lib" \
deps/go/go/bin/go test -run TestName ./internal/router/

Pure-Go packages (router, memory, mavweb, …) run under a plain go test ./pkg/.

The daemons (cmd/)

Binary	Role
mavend	Core. Router, phraser, memory, reminders, digestion tick. Owns the DB + IPC socket.
mavweb	HTTP UI + PWA (/dash, /history, /trace, /notifications, /tools); WebAuthn auth. Connects to mavend's socket.
mavsttd	Speech-to-text (whisper.cpp, CGO).
mavttsd	Text-to-speech (piper subprocess).
mavwaked	Wake-word / VAD gate.
mavenclient	Voice loop client (mic → stt → core → tts).
mavpoll	Telegram long-poll reach.
mavcaldav	CalDAV calendar sync.
mavmaild	Mail reader (IMAP, read-only). Holds the IMAP password; core never sees it.

Daemons are wired socket-to-socket, not linked. internal/ipc is the client/server wire protocol; the config in deploy/mavend.json (with ${VAR} env expansion from gitignored deploy/telegram.env) sets socket paths, model paths, and the phraser/embedder blocks.

Routing — read this before touching the router

internal/router/ has TWO layered engines. The LLM router is now the default and it is on in deploy — this section used to say it was wired nil, which stopped being true on 2026-07-31.

• LLM router (the intended design, REARCH.md): the resident Qwen3-1.7B (llmrouter.go) emits GBNF-constrained structured JSON, and the SAME model phrases replies. Embedder is demoted from a routing gate to a RAG hint. Wired at voice.go:214 via pickLLMRouter(cfg.Voice.UseLLMRouter(), llmClient); the flag is voice.llm_router (config.go), DefaultLLMRouter is on, and deploy/mavend.json sets it true.
• Classifier cascade (the failure floor, not dead code): classifier.go + embedder.go nearest-neighbour over frozen seed phrases. It runs when the LLM router is off, when there is no llama-server to talk to (pickLLMRouter logs that and degrades), and on any per-turn LLM error. Do not delete it — routing by seed similarity is the known cause of weak RU query handling, but a turn must never break on the model.

Cascade order: stage0.go exact-match fast-path → LLM router (when non-nil) → classifier fallback. Any LLM error falls through to the classifier so a turn never breaks on the model.

Measured on the 77-case RU fixture (MODEL-BAKEOFF-31-07-2026.md): the classifier scores 36.8% full accuracy at p50 31ms; Qwen3-1.7B scores 67.5% intent-only / 72.7% through the cascade at p50 ≈2.7s. Accuracy roughly doubled, latency is ~90× worse, and that trade was accepted deliberately. 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 #359. Fixed 31-07-2026 with structural signal (single-token utterance, keyless fact, act with no allowlisted fn) feeding the same stage-3 gate the classifier path already had — see gateLLMDecision in router.go. Note the second half of that bug: the LLM branch never consulted r.threshold at all, so a correct low confidence would have been discarded anyway.

Re-measured on the fixture after the fix: missed clarify 6/6 → 1, at the cost of 3 false clarifies and 2.6pt of full accuracy (72.7% → 70.1%, intent-only 67.5% → 74.0%). Two of the three false clarifies are acts the model mis-routed and the gate caught — asking beats wrongly executing, so the fixture and the daemon disagree about what is correct there. The third, "поужинал", was a real defect: the single-token rule was an English intuition and does not transfer to Russian, where one word is routinely a whole sentence.

Narrowed 01-08-2026. thinSingleToken (internal/router/singletoken.go) still thins a bare one-word nominal — "вода", "бэкап" — but spares two classes: a closed lexicon of social and control singles ("привет", "спасибо", "стоп", "yes"), and any token carrying a Russian verb ending (past tense, 2nd person, reflexive), because a verb already contains its subject. Both tests are offline and cost nothing. Re-measured: false clarifies 3 → 2, intent-only 74.0% → 75.3%, full accuracy unchanged at 70.1%, missed clarify still 1. The two remaining false clarifies are the act-with-no-allowlisted-fn arm of the gate, not this rule.

Agenda questions taken off the model, 01-08-2026. AgendaQueryGrammars (stage0.go, wired after the clock rules in buildRouter) routes "что у меня сегодня", "во сколько у меня встреча" and anything naming a calendar to IntentQuery at stage 0. They were going to IntentSystem, where replySystem has no agenda arm and answered "пока не умею" — the fixture had said query since ru-query-019 was written. Measured: full accuracy 70.1% → 72.7%, intent-only 75.3% → 77.9%, calendar 0/2 → 2/2, clarify counts unchanged. Note that Go's \b is ASCII-only and never fires after a Cyrillic letter; the pattern needs an explicit (\s|[?!.]|$).

LLM output contract

All phrasing paths emit {"response":"...","mood":"..."} (parsed in replier_llm.go and internal/phraser/llmphraser.go), with fallback to plain text and the legacy {"body","summary"}. Mood is a fixed enum. Router prompt is a separate contract: [{"intent":<enum>, key?, value?, text?, verb?}, ...], 7 intents (fact, reminder, note, query, act, chat, system). llm/check_prompt_parity.py in the training workspace enforces that the Go and relabelling prompts remain identical.

Non-goals (hard constraints)

Not a nag, not autonomous. Maven's persona is feminine — Russian self-reference must use feminine forms — рада, not рад; поняла, not понял. The owner is male and is addressed informally: "ты", singular, never "вы"/"ваш" and never "он"/"его" (she talks TO him, not about him). Pet names ("милый", "дорогой") are forbidden; his name ("Ками") is not. The eval enforces this: CheckAddress, CheckFeminine and CheckCringe in internal/phraser/eval/checks.go, scored by make eval-phrasing.

"Never phones home" is DEPRECATED (owner's call, 2026-07-31). It used to be a hard constraint and it is not one any more: a 0.8B — and a 1.7B — does not know enough to answer world questions, so she needs to read external sources. What replaces it:

• No telemetry, no cloud model, no third-party account. That part never changes. Nothing about Maven is reported to anyone, and inference stays on the box.
• Local sources first. Kiwix ZIMs on homesrv (Wikipedia, ifixit) before anything on the network. Reading beats recalling for a small model, and a local read costs nothing.
• External search is allowed and off unless configured, like the weather and telegram capabilities.
• His notes and facts are never search input. Looking up why the sky is blue and sending his stored personal notes to an upstream engine are different acts. Only the utterance goes out, never the persona block, history, or matched notes.

Web UI conventions

Server-rendered pages share cmd/mavweb/static/ui.css (served at /ui.css) and the nav partial (navHTML in cmd/mavweb/main.go, {{template "nav" "<active-page>"}}). No per-page <style> beyond true one-offs. Wrap every table in <div class=scroll> so wide data pans on a phone. Local preview + headless screenshot recipe is in AGENTS.md.

Vikunja

This repo is project Maven (ID 2) in Vikunja. MCP: http://localhost:9100/mcp (or http://192.168.1.104:9100/mcp from workpc). Feature/bug/deploy tasks go there.