rough-pizza-5956
07/25/2025, 9:59 AMtall-airline-16756
07/25/2025, 9:59 AMtall-airline-16756
07/25/2025, 10:01 AMaudio_source = rtc.AudioSource(
sample_rate=sample_rate,
num_channels=channels,
queue_size_ms=2000 # Increase from default to prevent overflow
)
• Adjust Voice Activity Detection (VAD) Sensitivity: Reduce the min_silence_duration to 0.3s to improve speech detection: vad_stream = VADStream(min_silence_duration=0.3)
• Modify Endpointing Delays: Reduce the min_endpointing_delay to make the agent more responsive: session = AgentSession(
min_endpointing_delay=0.3, # Reduce from default 0.5s
max_endpointing_delay=4.0, # Optionally reduce max delay
turn_detection="vad" # Explicitly set turn detection mode
)
• Increase Error Retry Limits: Configure the session to allow more retries for unrecoverable errors: conn_options = SessionConnectOptions(
max_unrecoverable_errors=5 # Increase from default 3
)
session = AgentSession(
conn_options=conn_options
)
• Enable Detailed Logging: Use logging to identify where capture failures occur in the pipeline.
• Monitor Silence Detection: Implement silence monitoring to detect when the agent becomes unresponsive: @agent.on("user_started_speaking")
def on_user_started_speaking(_msg: llm.ChatMessage):
user_last_spoke_time = time.time()
async def monitor_interaction():
while True:
if time.time() - user_last_spoke_time > SILENCE_THRESHOLD:
<http://logger.info|logger.info>("silent for too long! disconnecting")
await ctx.room.disconnect()
await asyncio.sleep(1)
These steps should help resolve the issue and improve the agent's responsiveness. Let me know if further assistance is needed.
Sources: livekit-agents/livekit/agents/voice/audio_recognition.py | Speech & Audio Processing | livekit/livekit_composite | DeepWiki