Commit Graph

12 Commits

Author SHA1 Message Date
kami 34521c30b8 Merge branch 'worktree-agent-ad5da57e47b822152' into overnight-jul31 2026-07-31 11:39:35 +04:00
kami f6d5a2a7a4 Swap the embedder to multilingual-e5-small (Vikunja #371, #372)
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
2026-07-31 11:38:18 +04:00
kami bf99fd4192 Add a voice.llm_router flag, default off
Wires cmd/mavend/voice.go to build the LLM router when the operator asks
for it. Default false, so nothing changes on the deploy box.
Look at pickLLMRouter: the flag on with no llama-server logs one line and
keeps the classifier, it never fails a turn.
The default stays off until the router can refuse (#359) and the extractor
runs on LLM decisions — both noted as TODOs in config.go.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 02:15:30 +04:00
kami 4595e0dffd Enable nudge digestion in the deployed config
Turns on the existing digest path on homesrv: a 30m batching window, at most 5
items per flush, and a severity ceiling of 2 so anything more urgent still
goes out immediately instead of waiting for the batch.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01X5JApcrCRVGmqrxnhynSik
2026-07-30 23:49:22 +04:00
kami 76a6a007ef Pin the resident model to Qwen3.5-0.8B and name Qwen3-1.7B as the target
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
2026-07-30 23:40:33 +04:00
kami 9876187721 Wire voice-tapped facts into entity resolution; fix phraser model config
WriteFactReq gains an optional Subject field (empty = old behavior,
no CoreAPI signature change) and the IntentFact handler now passes the
fact's key as its resolution subject, so voice-tapped facts flow into
the Vikunja #279 enrichment queue automatically.

Also: deploy/mavend.json's phraser was pointed at a 4B model with
n_gpu_layers=99, which OOM'd under memory pressure and left a zombie
llama-server child. Swapped to the 2B Qwen model matching the intended
resident-model size, keeping GPU offload.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018ghELqYhZNLub2TXGMazqA
2026-07-20 12:13:30 +04:00
kami 5fe8f228c1 feat(mavweb): /ecosystem page consuming Nexus/Praxis/Hexis + shell fixes
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>
2026-07-19 22:04:23 +04:00
kami 6a5121657a feat: {response,mood} output contract + router removal, TTS piper plan
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>
2026-07-11 22:51:50 +04:00
kami da60c14399 chore: docker, config, delivery sinks, dialogue, and agent docs
- Dockerfile: multi-stage build with CGO_ENABLED=0, embedder model copy,
  non-root user, healthcheck, and /data volume.
- docker-compose.yml: mavend + mavweb services with shared volume, health
  checks, and restart policy.
- .gitignore: ignore models/llm/*.gguf, deploy/telegram.env, tmp artifacts.
- deploy/mavend.json: add LLM, phraser, voice sections (embedder, model
  paths, wake sensitivity). Add telegram token env-var expansion.
- deploy/telegram.env.example: template for telegram bot token.
- internal/config/config.go: add LLM config struct, voice config struct
  (embedder, llama, wake sensitivity), telegram token loading.
- telegramsink: add chat intent delivery support alongside existing types.
- voicesink: skip empty payloads in delivery.
- dialogue/session: add chat intent to anaphora resolution, test coverage.
- AGENTS.md: update with LLM embedder, LFM model download/configure steps,
  new UI conventions.
- REARCH.md: architecture research document.
- cmd/mavend/main.go: wire LLM config, phraser, embedder, telegram config,
  WebAuthn, IPC event/routine handlers, and reactive notes.
2026-07-10 15:49:27 +04:00
kami 3b8fb691cb maven: seed safe tool allowlist (task 2)
- Add 12 homelab tools to deploy/mavend.json (6 read-only, 6 destructive)
- Add matching RU seed phrases to models/seeds/act.txt
- Guardrail verified: no destructive tool marked destructive=false

Scope: homelab. Read-only: status, ps, uptime, disk, memory, logs.
Destructive: restart, stop, start, docker-restart, docker-stop, reboot.

Co-Authored-By: opencode <opencode@anthropic.com>
2026-07-06 04:04:17 +04:00
kami 4c4b129789 deploy: wire voice in the container — bind + real onnxruntime 1.26
"voice unavailable" in the web UI: mavweb dials mavend:9100, but the container
mavend.json had no voice block, so mavend never bound 9100 (worked pre-docker
because the host's ~/.config/maven/mavend.json had one). Ported that block:
enabled, bind 0.0.0.0:9100 (not 127.0.0.1 — mavweb is a separate container),
lang ru, stt/tts worker sockets, onnx embedder.

Enabling the embedder surfaced a second bug: the router needs onnxruntime 1.26,
but deps/lib only carries dangling symlinks to it (absolute host paths, not in
the image), so the only libonnxruntime present was piper's 1.14 (copied in) →
"ORT API base: 2", crash loop. Fixed the Dockerfile to ship the real 1.26 .so
and stop copying piper's .so into the shared lib dir (piper finds its own 1.14
via $ORIGIN + exact soname, so TTS is unaffected).

Verified: mavend "onnx embedder loaded (384 dim)", "voice listening on :9100",
stack stable.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-03 23:07:59 +04:00
kami 04c8dd1406 deploy: dockerize — one image, one container per daemon
Compose stack replacing start-maven.sh's bare `&`-backgrounded processes.
Single multi-stage image builds all six daemons (CGO + prebuilt native libs
from deps/); compose runs one container each with a different command. Only
mavend mounts the encryption key (env_file, gitignored) and the db volume; the
modules mount just the shared unix-socket dir and read-only models — so the
"key-free modules" boundary is OS-enforced (separate namespaces), not just a
code convention. IPC stays unix-domain over a shared volume: zero code change,
paths move to /run/maven. Encrypted db at rest on a named volume, decrypted
working copy in tmpfs (RAM) per the at-rest encryption landed earlier.

Validated: `docker compose config` clean, mavend.json parses, all daemon flags
confirmed. NOT build-tested (no docker/GPU in authoring env) — deploy/README.md
lists the host-dependent tweak points (GPU passthrough, onnxruntime path,
cross-container voice bind, netdata host).

Chosen Docker over interim systemd units per the "dockerize soon" call — no
throwaway supervisor built.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-03 21:38:21 +04:00