111 lines
5.4 KiB
Python
111 lines
5.4 KiB
Python
"""Pure-text helpers for voice mode: Whisper hallucination filter, voice-chat
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stop phrases, and the TTS self-echo guard. No audio dependencies."""
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import difflib
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import re
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from contextlib import suppress
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from typing import Optional
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def _voice_config() -> dict:
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"""``voice`` section of config.yaml, or ``{}`` when missing, malformed, or the
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config system can't be imported (broken config mid-install)."""
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with suppress(Exception):
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from hermes_cli.config import load_config
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voice_cfg = load_config().get("voice", {})
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return voice_cfg if isinstance(voice_cfg, dict) else {}
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return {}
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# Whisper commonly hallucinates these phrases on silent/near-silent audio
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# (matched with trailing '.'/'!' stripped, so the bare form suffices).
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WHISPER_HALLUCINATIONS = {
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"thank you", "thanks for watching", "subscribe to my channel", "like and subscribe",
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"please subscribe", "thank you for watching", "bye", "you", "the end",
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# Non-English hallucinations (common on silence)
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"продолжение следует", "sous-titres", "sous-titres réalisés par la communauté d'amara.org",
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"sottotitoli creati dalla comunità amara.org", "untertitel von stephanie geiges",
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"amara.org", "www.mooji.org", "ご視聴ありがとうございました",
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}
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# Repetitive hallucinations (e.g. "Thank you. Thank you. Thank you.")
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_HALLUCINATION_REPEAT_RE = re.compile(r'^(?:thank you|thanks|bye|you|ok|okay|the end|\.|\s|,|!)+$',
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flags=re.IGNORECASE)
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def is_whisper_hallucination(transcript: str) -> bool:
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"""Check if a transcript is a known Whisper hallucination on silence."""
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cleaned = transcript.strip().lower()
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return (not cleaned or cleaned.rstrip('.!') in WHISPER_HALLUCINATIONS
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or bool(_HALLUCINATION_REPEAT_RE.match(cleaned)))
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DEFAULT_VOICE_STOP_PHRASES = ("stop",)
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def _load_voice_stop_phrases() -> tuple:
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"""Configured ``voice.stop_phrases`` (default ``("stop",)``); an empty tuple disables
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the feature. Malformed config (dict, list of non-strings) falls back to the default
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rather than crashing the voice loop."""
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with suppress(Exception):
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raw = _voice_config().get("stop_phrases", DEFAULT_VOICE_STOP_PHRASES)
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if isinstance(raw, str):
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raw = [raw]
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if isinstance(raw, (list, tuple)):
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return tuple(str(p).strip().lower() for p in raw if isinstance(p, (str, int, float)) and str(p).strip())
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return DEFAULT_VOICE_STOP_PHRASES
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def is_voice_stop_phrase(transcript: str, stop_phrases: Optional[tuple] = None) -> bool:
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"""True when *transcript* is EXACTLY a configured stop phrase. Deliberately strict: the whole
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utterance — lowercased, surrounding punctuation stripped — must equal a phrase, so "stop doing
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that and try again" still reaches the agent. ``voice.stop_phrases: []`` disables."""
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cleaned = transcript.strip().lower().strip(".,!?;: \t\n\"'") if transcript else ""
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return bool(cleaned) and cleaned in (_load_voice_stop_phrases() if stop_phrases is None else stop_phrases)
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# Similarity ratio (difflib.SequenceMatcher) above which a playback-phase barge transcript
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# is treated as a self-capture of Hermes' own TTS: the full-duplex listener has no echo
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# cancellation, so speaker bleed can be transcribed near-verbatim (TTS -> STT -> TTS loop).
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DEFAULT_TTS_ECHO_SIMILARITY_THRESHOLD = 0.6
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# Minimum normalized-transcript length before the sliding-window fallback runs. Below
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# this a genuine one-word barge-in ("yes") landing verbatim inside a longer reply would
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# score a trivial 1.0; a real self-capture spans pre-roll plus time-to-silence, so it is longer.
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# See #75792.
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MIN_FRAGMENT_LENGTH_FOR_ECHO = 10
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def _normalize_for_echo_compare(text: str) -> str:
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return re.sub(r"\s+", " ", text).strip().lower()
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def is_tts_echo(transcript: str, spoken_text: str,
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threshold: float = DEFAULT_TTS_ECHO_SIMILARITY_THRESHOLD) -> bool:
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"""True when *transcript* looks like a self-capture of *spoken_text*. Character-level similarity
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(language-agnostic): a genuine interjection rarely matches Hermes' own words, so a high ratio signals
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speaker-bleed (fail-closed guard for the playback-phase listener). Playback capture spans only pre-roll
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plus time-to-silence, so for long replies the transcript is a FRAGMENT and the whole-string ratio dilutes
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toward 0; when it misses, a transcript-sized window slides across `spoken_text`. Transcripts shorter than
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`MIN_FRAGMENT_LENGTH_FOR_ECHO` skip the fallback (a short interjection trivially matches a short window)."""
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a, b = _normalize_for_echo_compare(transcript or ""), _normalize_for_echo_compare(spoken_text or "")
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if not a or not b:
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return False
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def _similar(x: str, y: str) -> bool:
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return difflib.SequenceMatcher(None, x, y).ratio() >= threshold
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if _similar(a, b):
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return True
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if len(a) < MIN_FRAGMENT_LENGTH_FOR_ECHO or len(a) >= len(b):
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return False
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return any(_similar(a, b[start : start + len(a)]) for start in range(0, len(b) - len(a) + 1))
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def voice_stop_hint() -> str:
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"""One-line 'Say "stop" to end the voice chat.' hint for voice-mode start, using the first
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``voice.stop_phrases`` entry ("" when disabled). Every surface announcing voice-mode start
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(CLI, TUI, desktop) uses this one owner instead of hardcoding the wording."""
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phrases = _load_voice_stop_phrases()
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return f'Say "{phrases[0]}" to end the voice chat.' if phrases else ""
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