# 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 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 instead] → reply → 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). 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 # 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 # 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 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. - **`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`), `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 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`. - **`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. - **`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: 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. - **`updater.py`** — self-update from the Gitea releases API. Polls `/releases/latest` for a tag newer than `bolt_pet.__version__` and moves the checkout to it with `git fetch --tags` + `git checkout tags/`, 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. - **`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. 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. - **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//*.png` (filename-sorted, looping — currently Kenney's CC0 robot pack, see `assets/sprites/README.md`) and falls back to a procedurally-drawn placeholder blob per state if a folder has no frames; `tray.py` is the system tray menu (talk now / mute / nap / wander / click-through / history / wake-word tuning / quit) — the pet window has no title bar or taskbar entry; `history_window.py` and `wake_tuner.py` are the two dialogs it opens. ### 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. ## 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. Two newer features widen what leaves this machine, both switchable in `.env`: `SCREEN_CONTEXT` appends the focused window's *title* to each utterance (titles often contain file paths, document names, or subject lines), and `NOTIFICATION_BRIDGE` (off by default) forwards matching desktop notifications to the server. Neither sends screenshots or notification contents you haven't matched with `NOTIFICATION_FILTER`.