mARTin-B78
44ca0feabd
New GTK settings with a dropdown+editor pattern across four tabs: - Presets: select/add/delete prompt presets; edit name, keywords, hotkey, mode, per-preset model/temperature, and a clearly-bordered prompt textfield. - Engines: STT and LLM engine managers with green/red online-offline status dots, add/edit/delete, active selector, and an STT record-and-benchmark Test. - Input: input scheme + keys + quality-gate settings. - General: microphone picker with a live sounddevice level meter, output, language, notifications, launch-on-login toggle, and local-Whisper settings. Adds audio.py (mic enumeration via pactl + LevelMeter) and autostart.py (~/.config/autostart entry). Recorder + daemon honour the selected mic. Requirements gain sounddevice + tomli-w. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
286 lines
12 KiB
Python
286 lines
12 KiB
Python
"""Hotkey-driven engine: toggle recording per workflow, then transcribe + deliver.
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Used by the headless CLI (`run`) and the GTK GUI. A status callback lets the UI
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reflect each phase; desktop notifications fire regardless. Supports voice-keyword
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routing: one hotkey records, then the spoken keyword selects the preset.
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"""
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from __future__ import annotations
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import sys
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import threading
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from typing import Callable
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from . import llm, quality, stt
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from .config import Config, Workflow
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from .llm import LLMError
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from .notify import notify
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from .paste import active_window_id, deliver
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from .recorder import Recording, detect_recorder
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from .routing import route
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from .transcribe import Transcriber
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# status_cb(state, workflow_name, message)
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# state in {"loading", "idle", "recording", "busy", "done", "error"}
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StatusCallback = Callable[[str, str | None, str], None]
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class Daemon:
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def __init__(self, cfg: Config, status_cb: StatusCallback | None = None):
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self.cfg = cfg
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self.status_cb = status_cb
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self._lock = threading.Lock()
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self._recording: Recording | None = None
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self._active_workflow: Workflow | None = None
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self._target_window: str | None = None
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self._busy = False
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self._prepared = False
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self._listener = None
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# Synthetic preset used by the voice-routing hotkey.
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self._route_workflow = Workflow(name="Voice", hotkey=cfg.routing_hotkey, mode="route")
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self.recorder_name = detect_recorder(cfg.recorder)
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self.transcriber: Transcriber | None = None
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# -- feedback -------------------------------------------------------------
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def _notify(self, title: str, body: str = "", urgency: str = "normal") -> None:
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notify(title, body, urgency=urgency, enabled=self.cfg.notify)
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def _emit(self, state: str, workflow: str | None = None, message: str = "") -> None:
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if self.status_cb:
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try:
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self.status_cb(state, workflow, message)
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except Exception: # noqa: BLE001 - never let UI errors break the engine
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pass
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# -- model load (slow; call off the UI thread) ----------------------------
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def prepare(self) -> None:
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engine = self.cfg.active_stt
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if engine.is_local:
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model = engine.model or self.cfg.model
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self._emit("loading", None, f"Loading Whisper '{model}'…")
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self._notify("Loading model…", f"Whisper '{model}' ({self.cfg.device})")
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self.transcriber = Transcriber(
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model=model,
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device=self.cfg.device,
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compute_type=self.cfg.compute_type,
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beam_size=self.cfg.beam_size,
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)
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else:
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# Remote STT engine — no local model to load.
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self.transcriber = None
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self._emit("loading", None, f"Using {engine.name}")
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self._prepared = True
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self._emit("idle", None, "Ready")
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@property
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def ready(self) -> bool:
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return getattr(self, "_prepared", False)
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@property
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def is_recording(self) -> bool:
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return self._recording is not None
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# -- recording control ----------------------------------------------------
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def start_dictation(self, workflow: Workflow | None = None) -> None:
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wf = workflow or self._route_workflow
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with self._lock:
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if not self.ready or self._busy or self._recording is not None:
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return
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self._target_window = active_window_id()
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self._recording = Recording(self.recorder_name, self.cfg.mic)
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self._active_workflow = wf
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self._emit("recording", wf.name, "Recording…")
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self._notify(f"● {wf.name}", "Recording…")
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def finish_dictation(self, send_enter: bool = False) -> None:
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with self._lock:
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if self._recording is None:
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return
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rec, wf, win = self._recording, self._active_workflow, self._target_window
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self._recording = None
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self._active_workflow = None
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self._busy = True
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audio_path = rec.stop()
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threading.Thread(
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target=self._process, args=(audio_path, wf, win, send_enter), daemon=True
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).start()
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def cancel_dictation(self) -> None:
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with self._lock:
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if self._recording is None:
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return
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rec = self._recording
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self._recording = None
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self._active_workflow = None
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rec.discard()
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self._emit("idle", None, "Cancelled")
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self._notify("Cancelled", "Recording discarded.", "low")
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def toggle(self, workflow: Workflow) -> None:
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"""Start recording, or stop + process (used by GUI clicks and combos)."""
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if not self.ready:
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self._notify("Please wait", "Model still loading…", "low")
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return
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if self._busy:
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self._notify("Busy", "Still processing the last clip…", "low")
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return
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if self._recording is None:
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self.start_dictation(workflow)
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else:
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self.finish_dictation(send_enter=False)
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# -- worker ---------------------------------------------------------------
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def _process(self, audio_path, workflow: Workflow, window_id, send_enter: bool = False) -> None:
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label = workflow.name
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try:
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# Quality gate: drop silent / too-short clips before we even transcribe.
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duration, rms = quality.analyze_wav(audio_path)
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if quality.too_quiet(duration, rms,
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min_seconds=self.cfg.min_speech_seconds,
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silence_rms=self.cfg.silence_rms):
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self._emit("idle", label, "Too quiet")
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self._notify("Nothing heard", "No speech detected.", "low")
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return
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self._emit("busy", label, "Transcribing…")
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self._notify(f"⌛ {label}", "Transcribing…")
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hotwords = ", ".join(self.cfg.all_keywords) if workflow.mode == "route" else ""
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text = stt.transcribe(
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self.cfg.active_stt,
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audio_path,
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language=self.cfg.language,
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hotwords=hotwords,
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local_transcriber=self.transcriber,
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timeout=self.cfg.timeout,
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)
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text = quality.clean(text, strip_trailing_punctuation=self.cfg.strip_trailing_punctuation)
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if not text or (self.cfg.reject_hallucinations and quality.is_hallucination(text, duration)):
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self._emit("idle", label, "No speech detected")
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self._notify("Nothing heard", "No speech detected.", "low")
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return
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# Voice routing: pick the preset from a spoken keyword, strip it.
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if workflow.mode == "route":
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res = route(text, self.cfg.workflows, threshold=self.cfg.routing_threshold)
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target = self.cfg.preset_by_name(res.preset_name) or self.cfg.default_preset
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text = res.text
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label = target.name if target else "Transcribe"
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via = f"“{res.keyword}”" if res.keyword else "default"
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self._emit("busy", label, f"→ {label} ({via})")
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self._notify(f"🎙 {label}", f"matched: {via}")
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else:
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target = workflow
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if target and target.mode == "rewrite" and target.prompt:
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if not text:
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self._emit("idle", label, "Only a keyword heard")
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self._notify("Nothing to do", "Only the keyword was heard.", "low")
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return
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self._emit("busy", label, "Rewriting…")
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self._notify(f"⌛ {label}", "Rewriting…")
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try:
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text = llm.chat(
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self.cfg.active_llm,
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target.prompt,
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text,
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model=target.model or None,
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temperature=target.temperature,
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timeout=self.cfg.timeout,
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)
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except LLMError as exc:
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self._emit("error", label, str(exc))
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self._notify("Rewrite failed", str(exc), "critical")
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return
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if not text:
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self._emit("idle", label, "Nothing to type")
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return
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deliver(
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text,
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mode=self.cfg.output,
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window_id=window_id,
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type_delay_ms=self.cfg.type_delay_ms,
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)
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if send_enter:
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from .paste import press_enter
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press_enter(window_id)
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self._emit("done", label, text)
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self._notify(f"✓ {label}", text[:80] + ("…" if len(text) > 80 else ""))
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except Exception as exc: # noqa: BLE001 - surface any failure
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self._emit("error", label, str(exc))
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self._notify("Error", str(exc), "critical")
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print(f"[blitztext] error: {exc}", file=sys.stderr)
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finally:
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audio_path.unlink(missing_ok=True)
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with self._lock:
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self._busy = False
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self._emit("idle", None, "Ready")
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# -- hotkeys --------------------------------------------------------------
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def _build_mapping(self) -> dict:
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"""hotkey -> callback, skipping empty hotkeys, plus the routing hotkey."""
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mapping: dict = {}
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for wf in self.cfg.workflows:
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if wf.hotkey:
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mapping[wf.hotkey] = (lambda wf=wf: self.toggle(wf))
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if self.cfg.routing_enabled and self.cfg.routing_hotkey:
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mapping[self.cfg.routing_hotkey] = (lambda: self.toggle(self._route_workflow))
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return mapping
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def start_hotkeys(self):
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"""Register global hotkeys non-blocking; returns the pynput listener."""
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from pynput import keyboard
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self._listener = keyboard.GlobalHotKeys(self._build_mapping())
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self._listener.start()
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return self._listener
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def start_input(self):
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"""Start the configured input handler; returns its listener (joinable)."""
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if self.cfg.input_mode == "modifiers":
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from .inputmode import ModifierScheme
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self._scheme = ModifierScheme(
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self,
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start=self.cfg.key_start,
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stop=self.cfg.key_stop,
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send=self.cfg.key_send,
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cancel=self.cfg.key_cancel,
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push_to_talk=self.cfg.push_to_talk,
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)
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return self._scheme.start_listener()
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return self.start_hotkeys()
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def stop_input(self) -> None:
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scheme = getattr(self, "_scheme", None)
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if scheme is not None:
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scheme.stop_listener()
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self._scheme = None
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self.stop_hotkeys()
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def stop_hotkeys(self) -> None:
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if self._listener is not None:
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self._listener.stop()
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self._listener = None
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# -- headless run loop ----------------------------------------------------
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def run(self) -> None:
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self.prepare()
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if self.cfg.input_mode == "modifiers":
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scheme = "Ctrl+Win start · Ctrl stop+paste · Alt stop+paste+Enter · Esc cancel"
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print(f"[blitztext] ready. Recorder: {self.recorder_name}. Input: {scheme}", file=sys.stderr)
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else:
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lines = [f" {self.cfg.routing_hotkey} → Voice routing"] if self.cfg.routing_enabled else []
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lines += [f" {wf.hotkey} → {wf.name}" for wf in self.cfg.workflows if wf.hotkey]
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print(f"[blitztext] ready. Recorder: {self.recorder_name}. Hotkeys:\n" + "\n".join(lines), file=sys.stderr)
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self._notify("Blitztext ready", "Focus a text field and start dictating.")
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listener = self.start_input()
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try:
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listener.join()
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finally:
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self.stop_input()
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