kami/Maven

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kami d0afd9d4f6 Make Qwen3-1.7B the resident model

Stock Qwen3-1.7B, not the CPT'd one — that training is still running. It won
on both fixtures we have, measured tonight on an otherwise idle box:

  routing, 77 RU cases, intent-only:  67.5%  vs  59.7%  for Qwen3.5-0.8B
  talk fixture, 27 cases:             20/27  vs  11-17/27

It also beat Qwen3.5-2B, which is 20% larger, on every routing column.

Two other things came with it:

n_ctx goes 2048 -> 4096. This is a Thinking variant, so reasoning tokens need
the room, and 4096 is the context every score above was measured at. Shipping
2048 would ship something nobody measured.

The doc now says not to bother with sub-500M models, because I checked and they
are not close. LFM2.5-350M routes at 5.2% — worse than guessing among 7 intents
— and answers "столица Франции?" with "Сторзит", which is not a word. The 230M
replies to Russian in Spanish. Their published IFEval and BFCL numbers are good
and they are all English.

Note the routing gain needs the LLM router actually wired on to show up. It is
still nil, so this commit buys the phrasing improvement today and the routing
improvement when that lands.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ

2026-07-31 18:58:20 +04:00

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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 8 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.

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 and the committed default is an interim stopgap, not the intended design (see memory routing-architecture-target):

Target (REARCH.md): LLM-as-router. One 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.
Current stopgap: llmrouter is wired nil (around voice.go), so the classifier.go + embedder.go nearest-neighbour cascade actually runs. It routes by similarity to frozen seed phrases — the known cause of weak RU query handling.

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.

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 (the user is male; see memory maven-persona-gender).

"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.

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