internal/rss parses RSS 2.0 and Atom, and polls each configured feed on its own
interval; internal/webfetch is the one door either of them uses to touch the
network. The poller writes items as notes with source "rss:<feed>" and nothing
else: the answer path reads them back when he asks "что нового в лентах?", and
nothing is announced on arrival. A feed that dispatched would be a nag, which is
why the plan's breaking-news rule was left out rather than built.
webfetch is where the limits live, as code rather than a paragraph: http(s)
only, an allowlist (the configured feeds' hosts) and a denylist, a 2 MiB body
cap, a 3-redirect cap, one request per host per second, and a refusal to connect
to any private address — checked in the dialer's Control hook so it holds for
every resolved address and every redirect hop, not just for a literal IP.
Off unless configured: no "feeds" block, no poller, no outbound request. How far
a feed was read is a config fact (rss:latest:<name>), so a restart does not
re-note yesterday's headlines.
The digestion tick already runs the pattern detector over all recorded
events (67563ed) and writes a proposed_routines row. What was missing is
the other half of #247: a proposal that nobody is at the mic for reaches
nothing but the /routines page, so a pattern noticed at 03:00 is only
seen if he goes looking.
This wires the tick's proposals into the existing care-delivery path
rather than a second channel: sev1 nudge, loop.Gate, dispatcher, same
routing table as an accepted routine. Restraints, since a feature that
speaks unprompted is the easiest way to turn Maven into a nag:
- off unless configured — the new pattern_proposals block, absent by
default, and deploy/mavend.json ships notify: false;
- at most one announcement per tick however many patterns surfaced;
- at most one per cooldown (24h default) across all pairs;
- sev1, so quiet hours, away and snooze suppress it;
- suppressed means dropped, not queued — /routines still has it;
- once per pair for good, since proposed_routines is
UNIQUE(action, object) and the row survives dismissal.
The body is pattern.PhraseRoutine's literal Russian, not LLM-worded, so
an inferred routine cannot arrive describing something never observed.
Also raises pattern.MinEvents from 3 to 4 — the interval-quality item on
#43. Two intervals with a ±50% band is a coincidence with a mean, not a
pattern, and now that a scan of all history can announce itself the cost
of a false positive is a permanent dismissal of that pair.
The template's wildcard `listen 80` with no ACL was fixed in 50cc17f, but it
still only covered nexus/praxis/hexis. mavweb — the one service in the set
that serves an RCE surface (POST /tools defines argv internal/tool executes)
— had no block at all, so anyone wiring it up wrote their own, which is how
the wildcard got there the first time.
Adds a maven.kvmx.ru server with the same wg+LAN bind and allow/deny,
proxying 127.0.0.1:9201, with the WebSocket upgrade /ws needs, a 32m body
limit for push-to-talk PCM, and a 300s read timeout because an LLM turn on
the iGPU is slow.
Also records in deploy/ecosystem/docker-compose.yml that the sibling
`build:` paths pin nothing and ship the sibling working tree, with the
command to check what is about to be deployed. The stale public DNS records
(item 2) are outside the repo.
Verified: nginx -t on the template inside a minimal http{} accepts it.
The template said "drop into your nginx sites" but listened on the
wildcard `listen 80;` with no allow/deny ACL, unlike the actual deployed
hexis.kvmx.ru config which binds only to the WireGuard (10.42.0.1) and
LAN (192.168.1.104) addresses with allow/deny all. Anyone following the
template as written would expose these unauthenticated admin UIs to the
open internet.
Bind explicitly to those two addresses and add the matching ACL block,
mirroring cmd/mavweb/nginx.conf which already does this correctly.
Added a comment naming both addresses as host-specific so a deploy on a
different box swaps the IPs instead of reverting to `listen 80` when the
bind fails.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
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
DEPRECATION, flagged not asked: LLM-phrased nudges are no longer the default.
LLMPhraser.PhraseNudge now returns a hand-written Russian template. The model
still phrases chat, queries and reminders — only nudges moved.
Why: measured over many runs, Qwen3.5-0.8B wrote formal "вы" and plural
imperatives, used masculine self-reference, and invented facts and units
(90-95 seconds to boil an egg). A nudge is five words of known content, so
generation buys nothing and risks the persona every time. Templates score
15/15 on the nudge fixture, the model 11-13/15.
Nothing is deleted: the prompt, the fallbacks and the whole LLM nudge path
stay. Set phraser.llm_nudges = true in deploy/mavend.json to get them back.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
The e5 embedder puts every cosine in one narrow band (0.79-0.89), so the
absolute query_min_score gate cannot tell a real hit from a made-up
question: any value under the band answers everything, any value above it
answers nothing. False recall was 5/5.
New gate asks whether one note is clearly the best instead: top1 - top2 >
delta. New query_min_margin config knob, default 0.008, read off the sweep
in the recall harness. The absolute floor stays as a second check.
On the recall fixture with e5: answered 72% -> 68%, false recall 5/5 -> 1/5.
Vikunja #359
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
The two things that made this unsafe are fixed: the router can now
refuse, and slot extraction runs on its decisions.
On the held-out fixture it gets 63.2% of intents right against the
classifier's 50.0%, with no route errors. It costs about a second a
turn instead of 30ms.
The flag is a pointer now, so leaving it out of the config means on
and only writing false turns it off.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
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
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
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
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
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
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>
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>
"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>
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>
kami