Bolt-Pet/CLAUDE.md

# CLAUDE.md

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

## What this is

A desktop pet (PySide6 window) that is a voice/click UI on top of an external
Bolt server's desk API — same brain, memory, tools, and persona as that
server's Discord bot and Linux desk client. This repo has **no import
dependency** on the server repo; it's a standalone HTTP client configured via
its own `.env`.

Pipeline: `mic → openWakeWord ("thunderbolt", on-device) / push-to-talk /
click → record utterance → Deepgram STT → + active-window + screen-layout
context → POST /desk/converse → [server may relay a shell command to run on
this machine, or a `petctl` pseudo-command that moves/emotes the pet, jumps it
to another monitor, reads a screen's text back, or plays a multi-voice scene
instead] → reply (optionally tagged with a voice the server picked for it) →
ElevenLabs streaming TTS (or offline pyttsx3 fallback) → speakers`, with the
pet sprite/speech bubble reflecting state throughout, and playback
interruptible by talking over it (barge-in).

Because a relayed command's output goes back up the tool-result relay before
the final reply, a `petctl read` mid-turn means Bolt can look at a monitor and
then talk about what's on it in the same answer.

Side channels that let the pet act between turns: the heartbeat (proactive
announcements), the desktop notification bridge, and autonomous wandering —
all suppressed while it's napping (quiet hours / fullscreen DND).

## Commands

```bash
# Setup + run (creates .venv and installs requirements.txt on first run)
./run.sh          # macOS/Linux
run.bat           # Windows

# Preflight: is this install actually going to work? (config, mic, keys, sprites…)
python -m bolt_pet --doctor          # shallow: no network, no mic
python -m bolt_pet --doctor --deep   # contacts the server and opens the microphone

# Run tests (no pytest config file — tests self-insert repo root via sys.path).
# QT_QPA_PLATFORM=offscreen avoids a QApplication segfault on headless/no-display hosts.
QT_QPA_PLATFORM=offscreen .venv/bin/pytest tests/
.venv/bin/pytest tests/test_state.py::test_happy_path_transitions  # single test

# Redraw the pet's sprite frames (the committed PNGs are this script's output)
python scripts/generate_bolt_sprites.py             # --out /tmp/x to preview first

# Convert a grid sprite sheet into the per-frame-PNG convention sprite.py expects
python scripts/slice_spritesheet.py path/to/sheet.png assets/sprites/idle --cols 6 --rows 1
```

There is no lint/build step configured beyond pytest. `cp .env.example .env`
and fill in `BOLT_SERVER_URL` / `DESK_API_KEY` (+ `DEEPGRAM_API_KEY`,
`ELEVENLABS_API_KEY`) before running — without server config the controller
logs a missing-config message and exits its thread instead of starting.

## Architecture

- **`config.py`** — loads `.env` from the project root (not via python-dotenv;
  a small hand-rolled parser matching the server repo's `desk_client/bolt_desk.py`
  convention) into module-level constants. Everything else reads config from
  here, never `os.environ` directly.
- **`state.py`** — `PetStateMachine`, pure logic with no Qt/audio imports (kept
  that way deliberately for cheap unit testing). Enforces a transition table;
  notably `IDLE -> TALKING` is legal directly (no LISTENING/THINKING leg)
  because the heartbeat can make the pet speak proactively/unprompted.
- **`controller.py`** — `PetController(QObject)`, the pipeline orchestrator.
  Runs on a background `QThread` (wired in `ui/app.py`) so audio I/O/network
  never blocks the Qt event loop; communicates with the UI only through Qt
  signals (`state_changed`, `said`, `log`, `action`, `napping`), never touches
  a `QWidget` directly. Also drives the periodic heartbeat
  (`_maybe_heartbeat`, gated by `HEARTBEAT_INTERVAL_SECONDS`) which lets the
  server push proactive spoken announcements between user turns, and on the
  same tick re-evaluates nap state, checks for delivered files, and drains
  queued desktop notifications. It owns the live wake-word threshold
  (`wake_threshold()` is passed to `listen_for_wake_word` as a *callable* so
  the tray slider takes effect mid-listen) and the conversation `history`.
- **`server_client.py`** — HTTP client for the desk API, dependency-free
  beyond `requests` so it's easy to mock in tests. `converse()` loops relaying
  server-issued shell commands (`run_local_command`, executed via
  `subprocess.run(shell=True)` as the desktop user, 30s default timeout) via
  `/desk/tool_result` until the server sends a final `reply` (capped at
  `_MAX_RELAY_HOPS`). This is the same "full desktop control" trust model as
  the server repo's other desk clients — commands only ever originate from
  the user's own voice/click requests in their own session. A final reply is
  returned as a `Reply(text, voice_id, voice_name)` rather than a bare string,
  because the server can tag it with a voice — see "Voices" below.
  `list_outbox_files`
  / `download_outbox_file` hit the same `/desk/files` and `/desk/files/<id>`
  endpoints the server's `deliver_files` tool queues onto — see `file_delivery.py`.
- **`file_delivery.py`** — the filesystem half of receiving files the server
  queues via its `deliver_files` tool (`ai/desk_api.py` in the main tmn-api
  repo — "send me that report" during a conversation spools the matched
  workspace files, zipping multiple into one, onto the session's outbox).
  `controller._check_deliveries` lists `/desk/files` and downloads anything
  queued — right after a conversation/notification turn (the common case)
  and once per heartbeat tick for anything queued out-of-band — saving each
  under `DELIVERED_FILES_DIR` (default `~/Downloads/Bolt`). Downloading a
  file dequeues it server-side, so it's only ever handed out once; `save()`
  never overwrites an existing download, suffixing `" (1)"`, `" (2)"`, ... on
  a name collision. `sanitize_filename()` reduces a server-supplied name to
  its bare filename (`Path(...).name`), which is defense-in-depth against a
  delivered name that's secretly a path, since a per-user desk API key means
  the name isn't always coming from someone as trusted as the owner. Toggle
  off entirely with `RECEIVE_FILES=false`.
- **`audio/`** — `mic.py` (energy-based VAD utterance capture, ported from the
  server repo's `bolt_desk.py`), `wake_word.py` (openWakeWord `thunderbolt.onnx`
  detection + `NearMissLog` for threshold tuning — see below), `stt.py`
  (Deepgram), `tts.py` (ElevenLabs, streaming by default — `stream_pcm()` +
  `play_stream()` start playback on the first chunk; `chunks_to_int16()`
  carries odd bytes across HTTP chunk boundaries, without which everything
  after the first split sample plays as static — falling back to whole-clip
  PCM then offline `pyttsx3`; every entry point takes an optional `voice_id`
  overriding `ELEVENLABS_VOICE_ID`, and `model_for()` picks the multilingual
  model whenever there's an override or non-ASCII text, since the default
  `eleven_flash_v2` is English-only and would read either as garbled
  phonetic English rather than failing), `barge_in.py` (two detectors behind one
  `reset()`/`check()` shape, chosen by `BARGE_IN_MODE` via `make_detector`:
  **wake** (default) scores every frame with the same openWakeWord model the
  idle listener uses, so only the wake phrase cuts playback; **energy** is the
  original N-consecutive-loud-frames rule, threshold ~4x the VAD one because
  the mic hears the pet's own voice. Wake mode shares `_default_model` with
  the idle listener — the two never run concurrently — and `reset()`s it on
  detection so the tail of one reply can't count toward the next). Each
  accepts an injectable stream/model/protocol so tests don't need real audio
  hardware or a display.
- **`pet_actions.py`** — `petctl` pseudo-commands (`petctl move top-left`,
  `petctl emote wave`, `say`/`wander`/`nap`, the screen verbs
  `jump`/`monitors`/`read`, and `voice reset`). The desk API has no "move the pet" payload type
  and this repo can't change the server, so these ride the existing
  shell-command relay: `controller._handle_command` parses them and they never
  reach `subprocess`; anything else is a real shell command exactly as before.
  Pure parsing; the UI half is `PetWindow.apply_action`. Note `jump`'s target
  is *not* validated here — which monitors exist is a runtime fact this pure
  module doesn't have, so the spec passes through to `monitors.resolve()`.
  Query verbs (`monitors`, `read`) are answered in `_handle_command` rather
  than by `pet_actions.describe()`, because their output *is* the point: it
  goes back up the tool-result relay for Bolt to use in his reply — as is
  `voice reset`, which reports what it dropped since the server can't see
  which voice is in use. `voice` only ever resets: picking one is the
  server's job (`speak_as`, which it already knows how to use), so a
  `petctl voice <name>` attempt is an error pointing back at that marker.
- **`self_restart.py`** — `petctl self_restart`, the pet restarting itself so
  Bolt can *see* a code change he just made instead of waiting for a human to
  restart it. Three problems shape it, and all three are the interesting part.
  (1) The restart can't happen inline: killing the process mid-turn would drop
  the HTTP tool relay before the result was posted, leaving the server to wait
  out its timeout on a turn that can never finish — so the command only
  *arms* it (`controller._arm_self_restart`) and
  `controller._maybe_self_restart` fires it after the reply is spoken, the
  same "only between turns" rule the updater follows. (2) A broken edit must
  not be fatal, so `preflight()` imports the package in a **subprocess**
  before arming — this process holds the old modules, so an in-process import
  would pass on a file that no longer parses — and a SyntaxError comes back as
  the command's output, in the same turn, with the pet still running. (3) The
  reason has to outlive the process, so it's written to
  `~/.cache/bolt-pet/restart_context.json` (never inside the repo Bolt is
  editing) and read on the way back up by `controller._report_self_restart`,
  which posts it to the server as an ordinary turn — that's what makes
  "restart and check the sprites load" finish as a spoken sentence rather than
  a silence. `check_loop_guard` refuses after `SELF_RESTART_MAX` restarts in
  `SELF_RESTART_WINDOW_SECONDS`, so an edit-restart-crash cycle stops itself.
  Off switch: `SELF_RESTART=false`.
- **`dialogue.py`** — `dialoguectl` pseudo-commands: a multi-voice *scene*
  through ElevenLabs' Text to Dialogue endpoint (`audio/tts.
  synthesize_dialogue`), checked in `_handle_command` between petctl and
  filectl. Same single-line-JSON wire format as filectl and for the same
  reason (the server's `command` marker captures only up to the next
  newline), and it accepts the ElevenLabs field names (`inputs`/`voice_id`)
  as well as its own (`lines`/`voice`) because the model has read that API
  and copying its shape is the obvious thing to try. Voices are *named*
  (`DIALOGUE_VOICES` maps names to ids) rather than pasted as raw ids, and
  `self` resolves to whatever voice the pet is speaking with right now —
  including a `speak_as` pick — so Bolt sounds like himself in his own
  scenes. The API's limits (10 distinct voices, ~2000 characters) are
  enforced *before* the request so a mistake comes back up the tool-result
  relay as a sentence Bolt can act on rather than an HTTP 422 he can't see.
  Unlike the normal reply path there is no streaming variant, so a scene is
  whole-clip: `controller._play_dialogue` plays it with the same bubble,
  transcript and barge-in handling a spoken reply gets, and returns to
  THINKING afterwards (not IDLE) because the server is still waiting on the
  tool result — that leg is why `state.py` allows TALKING -> THINKING.
- **`file_ops.py`** — `filectl` pseudo-commands, checked in `_handle_command`
  right after petctl and before falling through to a real shell command.
  Executing arbitrary commands already worked via the shell relay
  (`run_local_command` — see `server_client.py` below); what filectl adds is
  a *reliable* way to do the read/write/edit/list slice of that, since
  getting the model to hand-roll a shell heredoc for multi-line content full
  of quotes/`$`/backticks is failure-prone — and `list` exists as its own op
  (rather than relying on the model shelling out to `ls`/`dir`) because this
  project is cross-platform and the model shouldn't have to guess which
  listing command applies on Windows vs. Linux vs. macOS; one glob-based op
  (`pattern`, default `*`; `recursive` for `rglob` instead of `glob`) covers
  all three. Wire format is `filectl <json>` where `<json>` is a
  **single-line** compact JSON object —
  `{"op": "list"|"read"|"write"|"edit", "path": ..., ...}` — not a multi-line
  marker block (an earlier design): the server relays this as the argument
  to the ordinary `command` tool marker, and that marker's extractor
  (`ai/agents/default.py` in the main repo) only captures up to the next
  newline, so anything genuinely multi-line silently got truncated no matter
  how the prompt worded it. JSON sidesteps that for free — `json.dumps`
  already encodes embedded newlines as the two characters `\n`, not a real
  line break, so multi-line file content still fits on the one physical line
  the extractor sees. `edit` requires the old text to match exactly once —
  same discipline as this project's own code-editing tool — and raises
  rather than guessing if it's missing or ambiguous. This doesn't expand
  what the server can do to this machine (a relayed shell command could
  already overwrite anything the desktop user can write — see the security
  notes below); it's a safer path to the same capability. Pure parsing
  (`parse`) is separated from the filesystem I/O (`execute`), matching
  pet_actions.py's parse/describe split.
- **`screen_context.py`** — active-window title (xprop/xdotool, Win32,
  osascript) appended to each utterance via `context_for()`, plus
  `is_fullscreen_active()` for do-not-disturb. Text only — the desk API takes
  no images. Every probe is best-effort and returns None/False rather than
  raising; the parsing is split into pure functions that are tested without a
  display server.
- **`monitors.py`** — the screen layout, and resolving `petctl jump` targets
  (a 1-based number, a name, `next`/`prev`/`primary`/`other`, or a direction
  like `left`/`up` worked out from the actual geometry). Pure — no Qt, no
  subprocess. The monitor list is *published by the UI*
  (`PetWindow.publish_monitors` builds it from `QGuiApplication.screens()` and
  emits it over a queued signal to `controller.set_monitors`), because the
  controller and the window must agree on what "monitor 2" means: enumerating
  with `xrandr` on one side and Qt's screen list on the other gives different
  orderings on the same machine, and Bolt would announce one screen and land
  on another. Qt is the single source of truth; `Monitor.index` is 0-based and
  `.number` is the 1-based value used in every string a human or the model
  sees. The controller resolves a jump to a concrete index *before* emitting
  it, so the window can't re-resolve against a different list.
- **`screen_text.py`** — OCR, so Bolt can read what's on a monitor
  (`petctl read [n|here|all]`). **Pull, not push**: nothing captures on its own
  — the server has to ask, and the text goes back as that command's output.
  That's deliberate; OCR of a 4K screen costs a second or two that would
  otherwise be added to *every* utterance, and screen contents leaving the
  machine should be a visible decision rather than a constant. Capture needs
  `mss` (X11/Win32/macOS, **not** Wayland), recognition needs Tesseract or
  RapidOCR; both are optional and soft-fail with a reason the way `hotkey.py`
  does, and `read_monitor()` never raises because its return value is command
  output. Engine selection takes injected probes so it's testable wherever.
- **`quiet.py`** — quiet-hours spec parsing (`23:00-08:00`, wraps midnight,
  comma-separated). Napping suppresses *proactive* noise and wandering only;
  wake word / click / push-to-talk still work.
- **`notifications.py`** — Linux/D-Bus notification bridge. Two latency/loss bugs
  fixed 2026-08-02, both in `controller._maybe_heartbeat`: draining was wired to the
  60s heartbeat interval rather than the ~1.2s wake tick, and a heartbeat that landed
  mid-conversation stamped its own clock *before* checking — burning the slot and
  waiting another full interval, repeatedly, which is how a notification could go
  unspoken for five or ten minutes. Draining now runs on every tick while IDLE, and the
  heartbeat clock only advances when the heartbeat actually runs. Separately, the rate
  limit used to *drop* notifications inside its window (a second text a minute later was
  silently lost); the filter still gates at queue time but the limit is gone — a burst
  is **batched into one turn** instead, same single round trip, no lost messages, capped
  by `_MAX_PENDING_NOTIFICATIONS`.
- **`notifications.py` internals** — tails
  `dbus-monitor`, parses Notify calls (pure `iter_notifications()`), filters
  and rate-limits them (`NotificationGate`), and the controller forwards
  survivors through `converse()`. Off by default — each one is a round trip.
- **`sudo_askpass.py`** — makes server-relayed `sudo` usable from a process
  with no terminal, by pointing sudo's `SUDO_ASKPASS` at a GUI helper and
  rewriting bare `sudo` to `sudo -A` (`add_askpass_flag`, a conservative regex
  that skips anything already carrying a flag and anything inside quotes).
  Prefers a real askpass binary and falls back to generating a
  zenity/kdialog wrapper in `~/.cache/bolt-pet/askpass.sh`. Resolution order
  is injectable (`is_executable`/`which`) so it's testable on a machine with a
  different set installed. See the security notes — the dialog is the boundary.
- **`updater.py`** — self-update from the Gitea releases API. Polls
  `<UPDATE_REPO_API>/releases/latest` for a tag newer than
  `bolt_pet.__version__` and moves the checkout to it with
  `git fetch --tags` + `git checkout tags/<tag>`, so "downloading an update"
  is just git and rolling back is one command. Three safety rules: a **dirty
  working tree is skipped, never stashed** (silently discarding your
  work-in-progress beats running an old version); everything after the
  checkout — dependency install, then an **import smoke test in a
  subprocess** (this process still has the old modules loaded, so importing
  in-process would prove nothing) — is guarded, and any failure rolls back to
  the exact ref that was live before, branch name or SHA; and the restart only
  happens once the new code imports, so a broken release costs a log line
  rather than a pet that won't start. Git goes through an injectable
  `run(args) -> (code, output)` callable so apply/rollback is unit-tested
  against a fake git; version comparison and release parsing are pure.
  `controller._maybe_update` drives it from the wake-listener tick (so the pet
  is IDLE and between turns by construction) and the actual `os.execv` happens
  in `ui/app.py` *after* `app.exec()` returns — that ordering is what
  guarantees the mic is released before the new process opens it.
- **`history.py`** — rolling transcript (`HISTORY_LIMIT` turns) behind the
  tray's History window and click-to-copy on the bubble.
- **`hotkey.py`** — global push-to-talk via `pynput`; soft-fails with a logged
  reason (Wayland, missing package, macOS permissions) since the wake word is
  the primary trigger.
- **`audio/stt_stream.py`** — streaming speech-to-text. The one-shot path waits for
  the utterance to end, uploads the whole WAV, then waits again; that second wait is
  dead time that grows with how long you spoke. Deepgram's live websocket removes it:
  `record_utterance(on_frame=...)` hands each captured frame to a
  `StreamingTranscriber`, so by the time the VAD decides you stopped the transcript is
  essentially already there. Three deliberate limits: `open()` returning **None is an
  ordinary outcome** (no websocket-client, no network, no key) because the full audio is
  still buffered and `controller._transcribe` just falls back; the **local VAD still
  decides when you stopped** rather than Deepgram's endpointing, since barge-in,
  follow-up listening and the grace period are all built on it and coupling them to the
  network is not a first-pass change; and the socket is **per-utterance**, because
  holding one open across an idle pet bills for silence and dies on the first blip.
  Off: `STT_STREAMING=false`.
- **Streamed replies** — `server_client.converse_stream()` reads NDJSON from the desk
  API's `/desk/converse_stream` and speaks each sentence as it arrives
  (`controller._speak_stream_chunk`), so the wait is time-to-first-sentence instead of
  the whole model call. `Reply.spoken` marks a reply whose sentences were already said:
  the text is still carried, because the follow-up rule needs to see whether it ended on
  a question, but it must not be read out again. A stream that fails *before* anything
  was spoken falls back to `converse()` invisibly; one that fails after ends the turn
  quietly rather than repeating the first half. Off: `STREAMING_REPLIES=false`.
- **`speech.py`** — everything the pet says, and the policy differences between
  kinds of saying. There were four near-copies of this in `controller.py` (a
  reply, a holding line, a streamed sentence, a dialogue scene), each repeating
  the same dance — transition state, show the bubble, maybe record history,
  reset barge-in, call TTS, reset barge-in *again*, resume state, decide
  whether to keep the mic open — and they had already drifted apart: one forgot
  to arm barge-in, another skipped the follow-up rule. Now the dance is
  `Speaker.say()` and the differences are data on a frozen `Utterance`
  (`record`, `resume`, `hold_talking`, `follow_up`, `interruptible`), built by
  the four classmethods `reply`/`holding`/`stream_chunk`/`scene`. Notable
  policies: a holding line is **not** recorded (it's filler; the transcript
  should keep the answer) and **not** interruptible (cutting off "give me a
  sec" strands the tool already running), and it resumes the state it
  interrupted rather than dropping to IDLE, because the turn isn't over. A
  streamed chunk stays TALKING so the sprite doesn't flicker between sentences.
  Collaborators are injected, so all of this is tested without Qt, audio or a
  real state machine. Two subtleties that are bugs waiting to happen: the
  barge-in detector is read through a **callable**, not held (it's built after
  the Speaker — it needs the mic stream — and swapped when the mode changes; two
  copies drifting apart is invisible until the wake model starts hearing the
  pet), and `last_detail` is captured *before* the post-playback reset, since
  reading it after means every interruption reports zeroed counters.
  `follow_up_decision()` is the mic-open rule as a pure function.
- **Lip-sync** — the mouth is driven by the audio, not a timer.
  `audio/tts.level_of(frame)` reduces a PCM frame to 0..1 loudness on a **sqrt
  curve** (speech sits well below peak most of the time, so a linear map leaves
  the mouth barely open during normal talking), `envelope()` does the same for a
  whole clip, and playback calls the `on_level` hook per chunk. That travels
  `Speaker` → `controller.mouth` (a Signal) → `PetWindow.set_mouth`, and
  `_mouth_frame()` indexes the talking frames directly — which works because
  `generate_bolt_sprites.py` draws them as an **openness ramp** (closed first,
  widest last) rather than an arbitrary loop. Levels going stale
  (`_MOUTH_STALE_SECONDS`) hands control back to the ordinary animation, so
  offline TTS — which has no envelope — degrades to the timed loop instead of
  freezing the mouth mid-syllable.
- **`window_state.py`** — where the pet was left, so it starts there.
  `~/.cache/bolt-pet/window.json`, atomic write on drag-end, every function
  swallows its own errors (a corrupt state file must mean the default corner,
  never a pet that won't start). `is_visible_on()` re-validates against the
  *current* screen layout on load, because the common case for a stale position
  is exactly the dangerous one: the pet was last on a monitor that is now
  unplugged, and restoring it faithfully puts it somewhere unreachable. Takes
  plain rectangles rather than importing Qt. Off: `PET_REMEMBER_POSITION=false`.
- **`doctor.py`** — `python -m bolt_pet --doctor`, a preflight, written after a
  week of debugging things one command would have shown: a venv whose python
  was a zero-byte file, an OCR engine never installed, a wrong proxy header.
  Twelve independent checks, each reporting ok / warn (degraded but working) /
  fail, and each saying **what to do about it** — `screen reading: warn` is
  useless alone, `apt install tesseract-ocr` is the whole point. Nothing raises:
  a doctor that crashes on a broken install is diagnosing the wrong patient, so
  `run()` catches per-check and a failed check becomes a FAIL row rather than a
  traceback. Shallow by default (no network, no mic) since it's the first thing
  you reach for when the network is what's broken; `--deep` actually contacts
  the server and opens the microphone.
- **`speech_text.py`** — sanitizes server replies before they're heard/shown.
  `for_speech()` (called inside `tts.speak()`, so every path to the speakers is
  covered) strips markdown, emoji, URLs and stray symbols the voice would read
  literally ("asterisk asterisk"), turns bullet lists into full sentences, and
  words a few symbols (`&` → "and"). `for_display()` is the looser version for
  the speech bubble — markdown syntax gone, emoji kept. `is_question()` decides
  whether a reply leaves the pet waiting on an answer: it tests the *spoken*
  form (so a '?' inside a stripped code block or URL doesn't count) and only a
  trailing one counts, since a question asked in passing isn't awaiting a
  reply. `speech.follow_up_decision` uses it to keep listening without the
  wake word, capped by `FOLLOW_UP_MAX_TURNS` so a server that ends every reply
  with a question can't loop forever off mic noise. Pure string logic, no
  Qt/audio imports.
- **`ui/`** — `app.py` wires `QApplication` + `PetWindow` + `PetTray` + the
  history/tuner windows + the push-to-talk hotkey + the controller thread
  together; `pet_window.py` is the frameless/translucent/always-on-top sprite
  window + speech bubble (non-square frames are centered in the square
  `PET_SIZE` window, see `paintEvent`), and also owns:
  - **wandering** — a ~30fps timer walks the window toward a random on-screen
    target every `PET_WANDER_INTERVAL_SECONDS` (randomized), suppressed
    whenever the pet is non-IDLE, napping, dragged, or has a bubble up. A
    commanded `petctl move` overrides all of that except the drag.
  - **the walk cycle** — while actually travelling, `_animation_key()` swaps
    the state animation for the side-view `walk/` frames (not a `PetState` —
    see the sprites README). It is stepped by *distance travelled*
    (`_WALK_PIXELS_PER_FRAME`), never by the animation timer, so the planted
    paw tracks backwards at exactly the speed the window moves forwards;
    `_advance_frame` deliberately no-ops while walking so the two can't
    double-step it. The art is drawn facing right and `_oriented()` mirrors it
    (cached per frame) when heading left. No `walk/` art → falls back to the
    old coded bob rather than a placeholder blob.
  - **emotes** — `emote_transform()` is pure maths (dx, dy, rotation, scale
    from a 0..1 progress) kept out of `paintEvent` so the curves are unit
    tested; every emote must return to the identity transform at progress 1.0
    or the pet ends up permanently askew.
  - **shaped input / click-through** — `PET_SHAPED_INPUT` masks the window to
    the sprite's opaque pixels so the square window's transparent corners stop
    eating clicks (mask rebuilt only when the frame changes, and pinned to the
    resting position so a bob/spin doesn't thrash it); `PET_CLICK_THROUGH`
    makes the pet ignore the mouse entirely.
  - **edge snapping** (`PET_EDGE_SNAP`) after a drag or a stroll, and **nap
    dimming** (`set_napping`).
  `sprite.py` loads `assets/sprites/<state>/*.png` (filename-sorted, looping —
  the art is *generated* by `scripts/generate_bolt_sprites.py`, a Pillow
  drawing of Bolt as a shepherd pup; edit the script and re-run it rather than
  the committed PNGs, see `assets/sprites/README.md`) and falls
  back to a procedurally-drawn placeholder blob per state if a folder has no
  frames. It also loads `EXTRA_ANIMATIONS` — currently just `walk/` — keyed by
  name rather than by `PetState`, with `has()` reporting whether a key is
  backed by real art so callers can decline a placeholder instead of trotting
  a blob across the desktop; `tray.py` is the system tray menu (talk now / mute / nap / wander /
  click-through / history / wake-word tuning / use-default-voice / quit) — the
  pet window has no title bar or taskbar entry; `history_window.py` and
  `wake_tuner.py` are the two dialogs it opens.

### Voices (the server's `speak_as`)

Ask Bolt to talk like someone else, or in another language, and the *server*
does the picking: its desk-only `voice_search` marker browses the ElevenLabs
voice library, and `speak_as: <voice_id>` on the final reply tags that reply
with the chosen voice (adding a Voice Library pick to the ElevenLabs account
first, so the id is usable by the time it reaches us). Nothing about that is
this repo's to decide — all the client owes it is actually speaking in the
voice it was handed: `converse()` returns it on `Reply`, `_apply_voice()`
records it, and `_speak()` passes it to `tts.speak(voice_id=...)`.

Two things are decided *here*, though, because the server can't:

- **The voice sticks** (`VOICE_STICKY`, default on). The server tags one
  reply and strips the marker before storing the turn, so it never sees the
  id again — "keep talking like that" would send it searching for a voice all
  over again, and it'd likely land on a different one. Holding the id
  client-side is what makes the rest of the conversation stay in that voice.
  An untagged reply therefore never *changes* the voice; only a new
  `speak_as`, `VOICE_STICKY=false`, or a reset does.
- **There's a way back.** Since the server was never told Bolt's own voice
  id, it can't ask for it back with `speak_as` — so reverting is local: the
  tray's **Use default voice** entry (enabled only while a picked voice is
  in use, kept in sync by the `voice_changed` signal), a restart, or
  `petctl voice reset`, which is what lets Bolt honour "go back to your
  normal voice" out loud. That last one needs the server's pet prompt block
  (`ai/desk_api.py`, `pet_tools`) to mention the verb, or the model never
  emits it — the desk API's prompt is where petctl is advertised.

### Wake-word detection

`audio/wake_word.py` uses a custom-trained openWakeWord model,
`thunderbolt.onnx` (ships in the project root), the same way the server
repo's `desk_client/bolt_desk.py` uses `bolt.onnx` for "hey bolt" — same
runtime (openWakeWord, ONNX inference framework), same per-frame
`predict()`/`reset()` loop. Every mic frame is scored; any class score at or
above `WAKE_WORD_THRESHOLD` (default `0.5`, in `.env`) counts as a
detection. Swap `WAKE_MODEL_FILE` to point at a differently-trained `.onnx`
model to change the wake phrase — everything downstream (STT, server call,
TTS) is unaffected.

**openwakeword's `Model.reset()` is not enough to forget a detection.** It
clears the *prediction* buffer only; the rolling audio window the classifier
actually scores lives in `model.preprocessor` (`raw_data_buffer` — 10s of raw
audio — plus `melspectrogram_buffer` and a ~120-frame `feature_buffer`) and
`AudioFeatures` has no reset method at all. So after a detection the wake
phrase is still in the window, and the next frame fed to the model re-fires on
it. Symptom when this bites: the pet cuts itself off a word into every reply,
because wake-mode barge-in resumes feeding the model and instantly matches the
"thunderbolt" that *started* the turn. `wake_word.hard_reset(model)` restores
the preprocessor to its as-constructed (silence) state and is what both
`listen_for_wake_word` and `WakeWordBargeIn.reset()` call — use it, not
`reset()`, anywhere a detection needs to be genuinely forgotten. The blank
state is cached on the preprocessor object (not in an `id()`-keyed dict —
CPython reuses ids after GC), since rebuilding it costs an ONNX pass over 10s
of silence.

The threshold is tunable at runtime: the tray's **Wake word tuning…** window
(`ui/wake_tuner.py`) shows the peak score seen and a rolling list of near
misses (frames within `WAKE_NEAR_MISS_MARGIN` *below* the threshold — i.e.
the times it nearly heard you), and its slider is read per frame because
`listen_for_wake_word` accepts a callable threshold. Set the threshold just
under the peak you can hit reliably, then persist it in `.env`.

### Testing conventions

`tests/` covers pure logic only (state machine, wake-word scoring loop, mic
VAD, HTTP client against mocks) — nothing there needs real audio hardware or
a display. Modules under test are written to accept fake streams/models/
`on_command` callables specifically to keep tests hardware-free; follow that
pattern (inject a `Protocol`-typed collaborator) rather than mocking at the
`sounddevice`/`openwakeword` import boundary when adding new testable logic.
`test_controller.py`, `test_controller_features.py`, `test_wander.py` and
`test_pet_window_features.py` need a `QApplication`, which segfaults without
a display unless run with `QT_QPA_PLATFORM=offscreen`.

Newer subsystems follow the same rule — the testable part is separated from
the part that needs hardware: dbus-monitor output is parsed by a pure
`iter_notifications(lines)`, xprop output by pure `parse_xprop_*` functions,
HTTP chunk reassembly by `chunks_to_int16`, emote motion by
`emote_transform`. Tests that touch the controller monkeypatch
`screen_context.context_for` / `is_fullscreen_active`, otherwise they shell
out to xprop on a headless box.

**`test_pipeline_smoke.py` is the exception, deliberately.** Unit tests inject
a fake at the seam they care about, and a run of production bugs — notifications
sitting unspoken for minutes, the pet saying things twice, `[laughing]` read
aloud, a device command arriving as prose — got through with every one of them
green, because each was an *interaction* between two individually-correct
units. So that file stands up a real threaded HTTP server on a loopback port,
speaks the desk protocol at it, and drives whole turns through the real
`server_client` (including NDJSON streaming), the real controller and the real
state machine, faking only the mic stream and the speakers. When a bug crosses
a module boundary, add the case there; when it lives inside one module, the
pure-function pattern above is still the cheaper test. It is also worth
mutation-checking a new case — break the source line it is meant to catch and
confirm it actually goes red.

## Security notes

The server can relay a shell command back to this machine to execute as the
desktop user (see `server_client.run_local_command`). This is intentional
("full desktop control" for things like "open firefox" or disk checks) and
matches the trust model of the server repo's other desk clients. Keep
`DESK_API_KEY` private and don't expose the desk API port to the open
internet.

`file_ops.py`'s `filectl` read/write/edit pseudo-commands ride that same
relay and are bound by the same trust model — no path is off-limits beyond
normal filesystem permissions for the desktop user, exactly like a relayed
`cat`/`sed`/`rm` already isn't. They don't grant the server anything a shell
command couldn't already do; they just make the read/write/edit path
reliable instead of relying on the model getting shell quoting right.

`sudo_askpass.py` widens that further, by design: with `SUDO_ASKPASS_PROMPT`
on (the default), a relayed bare `sudo` is rewritten to `sudo -A` and the
password is collected in a desktop dialog, so commands can escalate to root
instead of hanging on a tty the pet doesn't have. The dialog is the security
boundary — it's the only thing between the server deciding to run `sudo` and
it running, so the prompt is deliberately not suppressible per-command and
those commands get their own longer timeout (`SUDO_COMMAND_TIMEOUT_SECONDS`)
rather than being made non-interactive. Set `SUDO_ASKPASS_PROMPT=false` to
take the capability away entirely; sudo commands then fail. Note that
`sudo -n` / `sudo -A` / `sudo -u …` in a relayed command are never rewritten,
so an explicit non-interactive sudo stays non-interactive.

**Don't run the pet as root.** It needs no privileges of its own, PortAudio
can't reach the user's PipeWire socket from a root session (raw ALSA devices
reject the 16 kHz capture rate — `paInvalidSampleRate`), and every relayed
command would run unconstrained.

Several features widen what leaves this machine, all switchable in `.env`:
`SCREEN_CONTEXT` appends the focused window's *title* to each utterance
(titles often contain file paths, document names, or subject lines),
`MONITOR_CONTEXT` appends the screen layout (sizes and names only — no
contents), and `NOTIFICATION_BRIDGE` (off by default) forwards matching
desktop notifications to the server. None of those send screenshots or
notification contents you haven't matched with `NOTIFICATION_FILTER`.

`SCREEN_TEXT` is the biggest of them: `petctl read` OCRs a whole monitor and
sends the recognised text to the server — everything visible, not just the
focused window. Two things keep it honest. It's **pull-only**: no capture
happens unless the server explicitly asks, so it can't leak in the background
the way a per-turn annotation would, and each read is logged. And it is
strictly *not* a new capability — the shell relay could already run a
screenshot tool and pipe it through OCR — it just makes a thing the trust
model already allowed reliable, bounded (`SCREEN_TEXT_MAX_CHARS`) and
visible. It is nonetheless far easier to reach for than the shell route, so
if that trade isn't one you want, `SCREEN_TEXT=false` removes it and
`petctl read` starts reporting that it's disabled. Capture is `mss`-based and
therefore silently unavailable on Wayland.