mARTin-B78
34e4736080
One hotkey (Ctrl+Alt+Space) records; the spoken keyword at the start or end of speech selects the preset, which is then stripped and the rest applied. New routing.py does ASR-tolerant matching (normalize + fuzzy + edge-window scan + token-drift slack); config gains a [routing] section and per-preset `keywords`; the daemon adds a "route" mode and biases Whisper with the keywords as hotwords. Falls back to a default preset when no keyword is recognised. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
306 lines
11 KiB
Python
306 lines
11 KiB
Python
"""Configuration loading and the default config template."""
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from __future__ import annotations
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import os
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import tomllib
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from dataclasses import dataclass, field
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from pathlib import Path
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CONFIG_DIR = Path(os.environ.get("XDG_CONFIG_HOME", Path.home() / ".config")) / "blitztext"
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CONFIG_PATH = CONFIG_DIR / "config.toml"
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@dataclass
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class Workflow:
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name: str
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hotkey: str
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mode: str # "transcribe" | "rewrite"
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prompt: str = ""
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# Spoken trigger phrases for voice routing (matched at start/end of speech).
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keywords: list[str] = field(default_factory=list)
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# Optional per-workflow overrides of the [rewrite] defaults.
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model: str | None = None
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temperature: float | None = None
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# Cosmetic, used by the GUI.
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description: str = ""
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icon: str = "⚡"
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@dataclass
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class Config:
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# general
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recorder: str = "auto"
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output: str = "type" # type | paste
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type_delay_ms: int = 12
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notify: bool = True
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language: str = "de" # whisper hint; "" = autodetect
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# whisper
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model: str = "small"
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device: str = "auto" # auto | cuda | cpu
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compute_type: str = "auto" # auto | int8 | float16 | int8_float16
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beam_size: int = 5
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# rewrite (OpenAI-compatible)
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base_url: str = "https://api.openai.com/v1"
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api_key_env: str = "OPENAI_API_KEY"
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rewrite_model: str = "gpt-4o-mini"
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temperature: float = 0.3
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timeout: int = 45
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# voice-keyword routing
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routing_enabled: bool = True
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routing_hotkey: str = "<ctrl>+<alt>+<space>"
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routing_default: str = "" # preset name used when no keyword matches; "" = first
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routing_threshold: float = 0.82
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# workflows
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workflows: list[Workflow] = field(default_factory=list)
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def preset_by_name(self, name: str | None) -> "Workflow | None":
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if not name:
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return None
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return next((w for w in self.workflows if w.name == name), None)
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@property
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def default_preset(self) -> "Workflow | None":
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return self.preset_by_name(self.routing_default) or (self.workflows[0] if self.workflows else None)
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@property
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def all_keywords(self) -> list[str]:
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out: list[str] = []
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for w in self.workflows:
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out.extend(w.keywords)
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return out
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@property
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def api_key(self) -> str | None:
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return os.environ.get(self.api_key_env) or None
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def load(path: Path = CONFIG_PATH) -> Config:
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"""Load config from TOML, creating a default file on first run."""
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if not path.exists():
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ensure_default(path)
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with path.open("rb") as fh:
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data = tomllib.load(fh)
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g = data.get("general", {})
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w = data.get("whisper", {})
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r = data.get("rewrite", {})
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rt = data.get("routing", {})
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cfg = Config(
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recorder=g.get("recorder", "auto"),
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output=g.get("output", "type"),
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type_delay_ms=int(g.get("type_delay_ms", 4)),
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notify=bool(g.get("notify", True)),
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language=g.get("language", "de"),
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model=w.get("model", "small"),
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device=w.get("device", "auto"),
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compute_type=w.get("compute_type", "auto"),
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beam_size=int(w.get("beam_size", 5)),
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base_url=r.get("base_url", "https://api.openai.com/v1").rstrip("/"),
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api_key_env=r.get("api_key_env", "OPENAI_API_KEY"),
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rewrite_model=r.get("model", "gpt-4o-mini"),
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temperature=float(r.get("temperature", 0.3)),
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timeout=int(r.get("timeout", 45)),
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routing_enabled=bool(rt.get("enabled", True)),
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routing_hotkey=rt.get("hotkey", "<ctrl>+<alt>+<space>"),
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routing_default=rt.get("default", ""),
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routing_threshold=float(rt.get("threshold", 0.82)),
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)
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for entry in data.get("workflow", []):
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cfg.workflows.append(
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Workflow(
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name=entry["name"],
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hotkey=entry.get("hotkey", ""),
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mode=entry.get("mode", "transcribe"),
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prompt=entry.get("prompt", ""),
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keywords=list(entry.get("keywords", [])),
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model=entry.get("model"),
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temperature=entry.get("temperature"),
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description=entry.get("description", ""),
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icon=entry.get("icon", "⚡"),
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)
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)
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if not cfg.workflows:
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raise ValueError(f"No [[workflow]] entries defined in {path}")
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return cfg
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def save(cfg: Config, path: Path = CONFIG_PATH) -> None:
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"""Write the config back to TOML (used by the settings UI).
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Note: inline comments from the template are not preserved on save.
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"""
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import tomli_w
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data: dict = {
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"general": {
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"recorder": cfg.recorder,
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"output": cfg.output,
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"type_delay_ms": cfg.type_delay_ms,
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"notify": cfg.notify,
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"language": cfg.language,
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},
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"whisper": {
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"model": cfg.model,
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"device": cfg.device,
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"compute_type": cfg.compute_type,
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"beam_size": cfg.beam_size,
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},
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"rewrite": {
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"base_url": cfg.base_url,
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"api_key_env": cfg.api_key_env,
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"model": cfg.rewrite_model,
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"temperature": cfg.temperature,
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"timeout": cfg.timeout,
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},
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"routing": {
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"enabled": cfg.routing_enabled,
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"hotkey": cfg.routing_hotkey,
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"default": cfg.routing_default,
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"threshold": cfg.routing_threshold,
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},
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"workflow": [],
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}
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for wf in cfg.workflows:
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entry: dict = {"name": wf.name, "hotkey": wf.hotkey, "mode": wf.mode}
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if wf.keywords:
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entry["keywords"] = wf.keywords
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if wf.prompt:
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entry["prompt"] = wf.prompt
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if wf.model:
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entry["model"] = wf.model
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if wf.temperature is not None:
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entry["temperature"] = wf.temperature
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if wf.description:
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entry["description"] = wf.description
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if wf.icon and wf.icon != "⚡":
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entry["icon"] = wf.icon
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data["workflow"].append(entry)
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path.parent.mkdir(parents=True, exist_ok=True)
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with path.open("wb") as fh:
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tomli_w.dump(data, fh)
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def ensure_default(path: Path = CONFIG_PATH) -> Path:
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path.parent.mkdir(parents=True, exist_ok=True)
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if not path.exists():
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path.write_text(DEFAULT_CONFIG, encoding="utf-8")
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return path
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# Hotkey syntax is pynput's GlobalHotKeys format, e.g. "<ctrl>+<alt>+space".
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DEFAULT_CONFIG = """\
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# Blitztext for Linux — configuration
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# Hotkey format follows pynput: <ctrl> <alt> <shift> <cmd> + a letter/keyname.
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# Each hotkey TOGGLES recording: press to start speaking, press again to finish.
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[general]
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recorder = "auto" # auto | pw-record | parecord | arecord
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output = "type" # "type" = xdotool types it; "paste" = clipboard + Ctrl+V
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type_delay_ms = 12 # per-keystroke delay for xdotool type (raise if chars drop)
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notify = true # desktop notifications for each phase
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language = "de" # Whisper language hint; "" = autodetect
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[whisper]
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model = "small" # tiny | base | small | medium | large-v3, or a local path
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device = "auto" # auto | cuda | cpu (auto tries cuda, falls back to cpu)
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compute_type = "auto" # auto | int8 | float16 | int8_float16
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beam_size = 5
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[rewrite]
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# OpenAI-compatible chat endpoint. Define your own provider/API/model here.
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# Point base_url at OpenAI, OR any local server that speaks the OpenAI chat API
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# (vLLM, llama-swap, Ollama's /v1, LM Studio, ...). Examples:
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# base_url = "https://api.openai.com/v1" (OpenAI)
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# base_url = "http://localhost:8000/v1" (local vLLM / llama-swap)
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# api_key_env names the ENV VAR holding the key (local servers often ignore it).
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base_url = "https://api.openai.com/v1"
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api_key_env = "OPENAI_API_KEY"
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model = "gpt-4o-mini" # default model for rewrite workflows
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temperature = 0.3
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timeout = 45
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[routing]
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# Voice-keyword routing: ONE hotkey to dictate. Say a preset's keyword at the
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# START or END of your speech and that preset is applied; otherwise the default
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# preset is used. (Per-preset hotkeys below still work as direct shortcuts.)
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enabled = true
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hotkey = "<ctrl>+<alt>+<space>"
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default = "Transcribe" # preset used when no keyword is recognised
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threshold = 0.82 # 0..1 fuzzy-match strictness (higher = stricter)
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# ----------------------------------------------------------------------------
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# Workflows / presets. mode = "transcribe" types the raw transcript. mode =
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# "rewrite" sends it through the LLM with `prompt` as the system prompt.
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# keywords = spoken trigger phrases for voice routing (start or end of speech)
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# hotkey = optional direct global hotkey ("" = none; voice routing is primary)
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# A workflow may override the [rewrite] defaults with its own model/temperature.
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# ----------------------------------------------------------------------------
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[[workflow]]
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name = "Transcribe"
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icon = "⚡"
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description = "Speak, get plain text."
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hotkey = ""
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mode = "transcribe"
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[[workflow]]
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name = "Nicer email"
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icon = "✉"
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description = "Rough notes → polished email."
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keywords = ["nicer email", "bessere email", "schöne mail"]
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hotkey = "<ctrl>+<alt>+e"
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mode = "rewrite"
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prompt = '''Du bist ein Schreibassistent fuer E-Mails. Du erhaeltst ein gesprochenes Transkript.
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Schreibe daraus eine freundliche, gut formulierte und etwas ausfuehrlichere E-Mail:
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- Korrigiere Rechtschreibung und Grammatik
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- Formuliere hoeflich, klar und professionell
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- Ergaenze sinnvolle Hoeflichkeitsfloskeln (Anrede/Gruss), wenn passend
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- Behalte die urspruengliche Aussage und Absicht bei, erfinde keine Fakten
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- Antworte in der Sprache des Transkripts
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- Gib NUR den E-Mail-Text zurueck, keine Erklaerungen'''
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[[workflow]]
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name = "Improve text"
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icon = "✨"
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description = "Speak → cleaner writing."
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keywords = ["improve text", "verbessere text", "bessere schreibweise"]
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hotkey = "<ctrl>+<alt>+i"
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mode = "rewrite"
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prompt = '''Du bist ein Lektor und Schreibassistent. Verbessere den folgenden gesprochenen Text:
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- Korrigiere Rechtschreibung und Grammatik
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- Verbessere Formulierung und Lesefluss, behalte die Bedeutung bei
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- Antworte in der Sprache des Transkripts
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- Gib NUR den verbesserten Text zurueck, keine Erklaerungen'''
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[[workflow]]
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name = "Calm down"
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icon = "☺"
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description = "Frustrated in → calm out."
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keywords = ["calm down", "beruhige das", "entspannte nachricht"]
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hotkey = "<ctrl>+<alt>+c"
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mode = "rewrite"
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prompt = '''Du erhaeltst ein gesprochenes, frustriertes oder veraergertes Transkript.
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Formuliere es in eine ruhige, sachliche und hoefliche Nachricht um, die dasselbe
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Anliegen professionell vermittelt. Antworte in der Sprache des Transkripts.
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Gib NUR die umformulierte Nachricht zurueck, keine Erklaerungen.'''
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[[workflow]]
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name = "Add emojis"
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icon = "✿"
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description = "Text in → emojis out."
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keywords = ["add emojis", "mit emojis", "emojis dazu"]
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hotkey = "<ctrl>+<alt>+j"
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mode = "rewrite"
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prompt = '''Du erhaeltst ein gesprochenes Transkript. Gib den Text moeglichst originalgetreu
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zurueck, fuege aber regelmaessig passende Emojis ein (etwa alle 1-2 Saetze).
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Korrigiere offensichtliche Fehler, behalte Stil und Bedeutung bei.
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Gib NUR den Text mit Emojis zurueck, keine Erklaerungen.'''
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"""
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