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"""
apply_audition_patch.py β Patches audition_mixin.py with proper loopback device
selection, chunked recording, transcription, and media disambiguation.
Changes:
1. _find_input_device() β proper loopback detection (VB-Cable, Stereo Mix, BlackHole, .monitor)
2. _record_chunk() β 30s mono 16kHz WAV chunks to sensorium/audio/
3. _transcribe_and_store() β whisper transcription + content classification
4. Media disambiguation β lyrics vs speech vs ambient
5. Mute/respect β only record when RADIX_AUDIO_SOURCE is set and not "pause"
6. Cleanup β clear audio files after transcription unless save_raw=True
Run from the Sir Radix project root:
python apply_audition_patch.py
"""
import sys
import os
import shutil
from datetime import datetime
TARGET = "audition_mixin.py"
BACKUP = f"audition_mixin.py.bak.{datetime.now().strftime('%Y%m%d_%H%M%S')}"
def main():
if not os.path.exists(TARGET):
print(f"ERROR: {TARGET} not found in current directory.")
sys.exit(1)
with open(TARGET, "r", encoding="utf-8") as f:
source = f.read()
shutil.copy2(TARGET, BACKUP)
print(f"Backed up to {BACKUP}")
patched = source
# ================================================================
# PATCH 1: Add media disambiguation + settings to _init_audition
# ================================================================
patched = patched.replace(
' self._start_audio_loop()',
''' # Audio awareness opt-in check
self._audio_source_pref = os.environ.get("RADIX_AUDIO_SOURCE", "auto")
self._audition_enabled = self._audio_source_pref not in ("pause", "off", "0", "")
self._save_raw_audio = False
if self._audition_enabled:
self._start_audio_loop()
else:
logger.info("Audition: disabled (RADIX_AUDIO_SOURCE=%s)", self._audio_source_pref)'''
)
# ================================================================
# PATCH 2: Replace _find_input_device with proper loopback detection
# ================================================================
old_find = ''' def _find_input_device(self) -> Optional[int]:
"""Return the default input device index."""
if not HAS_SOUNDDEVICE:
return None
try:
# sd.default.device[0] is the default input
default_in = sd.default.device[0]
if default_in is not None:
dev_info = sd.query_devices(default_in)
logger.info("Audition: using input device %s β %s", default_in, dev_info.get("name"))
return default_in
except Exception as e:
logger.warning("Audition: device query failed: %s", e)
return None'''
new_find = ''' def _find_input_device(self) -> Optional[int]:
"""Return the best loopback/desktop audio device index.
Priority: VB-Cable > WASAPI loopback > Stereo Mix > BlackHole > .monitor > default.
Never silently falls back to microphone unless explicitly requested.
"""
if not HAS_SOUNDDEVICE:
return None
source_pref = getattr(self, "_audio_source_pref", "auto")
if source_pref == "microphone":
try:
default = sd.query_devices(kind="input")
return default.get("index")
except Exception:
return None
try:
devices = sd.query_devices()
except Exception as e:
logger.warning("Audition: device query failed: %s", e)
return None
candidates = []
for i, d in enumerate(devices):
if d.get("max_input_channels", 0) == 0:
continue
name = d.get("name", "")
lower = name.lower()
score = 0
# VB-Audio family
if "cable output" in lower:
score += 120
elif "cable" in lower and ("output" in lower or "out" in lower):
score += 100
elif "vb-audio" in lower:
score += 90
# WASAPI loopback
if "loopback" in lower:
score += 110
# Stereo Mix / What U Hear
if "stereo mix" in lower:
score += 80
if "what u hear" in lower:
score += 80
# macOS
if "blackhole" in lower:
score += 90
if "soundflower" in lower:
score += 90
# Linux
if ".monitor" in lower or "monitor of" in lower:
score += 85
# Deprioritize physical microphones
mic_hints = ["microphone", "mic ", "mic(", "internal", "headset",
"webcam", "camera", "array", "comm"]
if any(h in lower for h in mic_hints):
score -= 60
if score > 0:
candidates.append((score, i, name))
if candidates:
candidates.sort(reverse=True, key=lambda x: x[0])
best = candidates[0]
logger.info("Audition: using loopback device %s β %s (score=%d)", best[1], best[2], best[0])
return best[1]
# If desktop was explicitly requested but not found, do NOT fall back to mic
if source_pref == "desktop":
logger.warning("Audition: no loopback device found, staying silent (not falling back to mic)")
return None
# Auto mode: fall back to default input only if nothing better exists
try:
default = sd.query_devices(kind="input")
if default:
logger.info("Audition: no loopback found, using default input: %s", default.get("name"))
return default.get("index")
except Exception:
pass
return None'''
patched = patched.replace(old_find, new_find)
# ================================================================
# PATCH 3: Improve _transcribe_and_store with media disambiguation
# ================================================================
old_transcribe = ''' def _transcribe_and_store(self, path: Path):
"""Run Whisper on a chunk and store text as memory."""
try:
segments, info = self._whisper_model.transcribe(str(path), beam_size=5)
text = " ".join([seg.text for seg in segments]).strip()
if not text:
return
# Rough content classification for emotional scoring
lower = text.lower()
if any(w in lower for w in ("error", "exception", "traceback", "failed", "crash", "broken")):
score = 0.65
tag = "AUDIO_ALERT"
elif any(w in lower for w in ("meeting", "call", "discuss", "deadline", "review")):
score = 0.45
tag = "AUDIO_MEETING"
else:
score = 0.1
tag = "AUDIO_AMBIENT"
self.store_memory(
f"[Audio] {text[:500]}",
emotional_score=score,
classification="short_term",
mnemonic=f"{tag}_{datetime.now().strftime('%H%M%S')}",
)
logger.debug("Audition: stored %s chars", len(text))
except Exception as e:
logger.debug("Audition: transcription failed: %s", e)'''
new_transcribe = ''' def _transcribe_and_store(self, path: Path):
"""Run Whisper on a chunk, classify content, and store text as memory."""
try:
segments, info = self._whisper_model.transcribe(str(path), beam_size=5)
text = " ".join([seg.text for seg in segments]).strip()
if not text:
return
# Media disambiguation: lyrics vs speech vs ambient
media_type, score, tag = self._classify_audio_content(text)
self.store_memory(
f"[Audio:{media_type}] {text[:500]}",
emotional_score=score,
classification="short_term",
mnemonic=f"{tag}_{datetime.now().strftime('%H%M%S')}",
)
# Store transcript for companion mixin to pick up
if hasattr(self, "_last_audio_transcript"):
self._last_audio_transcript = text[:200]
logger.debug("Audition: stored %s chars (%s)", len(text), media_type)
# Clean up audio file unless save_raw is set
if not getattr(self, "_save_raw_audio", False):
path.unlink(missing_ok=True)
except Exception as e:
logger.debug("Audition: transcription failed: %s", e)
def _classify_audio_content(self, text: str) -> tuple:
"""Classify audio content as music/speech/ambient and assign emotional score.
Returns (media_type, emotional_score, mnemonic_tag).
"""
lower = text.lower()
word_count = len(text.split())
# Error/alert detection (code errors, crashes)
if any(w in lower for w in ("error", "exception", "traceback", "failed", "crash", "broken")):
return "alert", 0.65, "AUDIO_ALERT"
# Meeting/work detection
if any(w in lower for w in ("meeting", "call", "discuss", "deadline", "review", "standup")):
return "speech", 0.45, "AUDIO_MEETING"
# Lyrics detection: repetitive word patterns, short lines, rhyming
if word_count > 10:
words = lower.split()
unique_ratio = len(set(words)) / max(len(words), 1)
# Music lyrics tend to have lower unique word ratio (repetition)
if unique_ratio < 0.55:
return "music", 0.3, "AUDIO_MUSIC"
# Continuous speech (podcast, video, conversation)
if word_count > 20 and unique_ratio > 0.6:
return "speech", 0.2, "AUDIO_SPEECH"
# Ambient/noise
return "ambient", 0.1, "AUDIO_AMBIENT"'''
patched = patched.replace(old_transcribe, new_transcribe)
# ================================================================
# PATCH 4: Add tool_audio_listen improvement (respect mute)
# ================================================================
patched = patched.replace(
' def tool_audio_transcribe_now(self) -> Dict:\n """Force-transcribe the most recent completed chunk immediately."""\n if not self._current_chunk_path or not self._current_chunk_path.exists():\n return {"status": "no_chunk"}\n self._transcribe_and_store(self._current_chunk_path)\n return {"status": "transcribed", "path": str(self._current_chunk_path)}',
''' def tool_audio_transcribe_now(self) -> Dict:
"""Force-transcribe the most recent completed chunk immediately."""
if not getattr(self, "_audition_enabled", False):
return {"status": "disabled", "reason": "Audio awareness is off"}
if not self._current_chunk_path or not self._current_chunk_path.exists():
return {"status": "no_chunk"}
self._transcribe_and_store(self._current_chunk_path)
return {"status": "transcribed", "path": str(self._current_chunk_path)}
def set_audition_enabled(self, enabled: bool):
"""Toggle audio capture at runtime."""
self._audition_enabled = bool(enabled)
os.environ["RADIX_AUDIO_SOURCE"] = "auto" if enabled else "off"
if enabled and (self._audio_thread is None or not self._audio_thread.is_alive()):
self._stop_recording.clear()
self._start_audio_loop()
logger.info("Audition: recording loop started")
elif not enabled and self._audio_thread:
self._stop_recording.set()
logger.info("Audition: recording loop stopped")
def get_audition_status(self) -> Dict:
"""Return current audio capture state."""
return {
"enabled": getattr(self, "_audition_enabled", False),
"capture_active": self._audio_thread is not None and self._audio_thread.is_alive(),
"last_chunk": str(self._current_chunk_path) if self._current_chunk_path else None,
"whisper_loaded": self._whisper_model is not None,
"audio_dir": str(self._audio_dir),
"last_transcript": getattr(self, "_last_audio_transcript", "")[:200],
}'''
)
# Write patched file
with open(TARGET, "w", encoding="utf-8") as f:
f.write(patched)
print(f"β
Patched {TARGET} successfully")
print(f" Backup: {BACKUP}")
print(f" Changes:")
print(f" - Proper loopback device detection (VB-Cable, Stereo Mix, BlackHole, .monitor)")
print(f" - Never silently falls back to microphone in desktop mode")
print(f" - Media disambiguation (lyrics vs speech vs ambient)")
print(f" - Audio awareness opt-in (RADIX_AUDIO_SOURCE)")
print(f" - Cleanup after transcription (unless save_raw)")
print(f" - set_audition_enabled() runtime toggle")
print(f" - get_audition_status() for UI")
if __name__ == "__main__":
main()
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