ancient-iron-20196
09/19/2025, 11:56 AMtall-airline-16756
09/19/2025, 11:56 AMtall-airline-16756
09/19/2025, 11:57 AMdeleteRoom API. For instance, you might schedule a task to delete the room after 5 minutes (300 seconds).
• Custom Monitoring: Another approach is to create a monitoring loop that keeps an eye on user activity and disconnects the room after a timeout period, like 5 minutes of inactivity.
If you'd like, I’d be more than happy to walk you through the details of implementing either method. Just let me know how I can support you!
Sources: livekit-agents/livekit/agents/utils/connection_pool.py | Inside a session | LiveKit Docs | SIP APIs | LiveKit Docs | Speech & Audio Processing | livekit/livekit_composite | DeepWikiancient-iron-20196
09/19/2025, 11:58 AMtall-airline-16756
09/19/2025, 11:59 AMempty_timeout and departure_timeout. These help control how long a room stays active when no participants are around or after everyone leaves.
To enforce session limits, a great approach is to add some custom logic at the application level. For example, you could use tokens with time-to-live (TTL) settings or programmatically delete rooms after a certain time using the Server API.
If you'd like, I’m here to help you set up these configurations or guide you through implementing a custom solution. Just let me know!
Sources: server/index.js | pkg/config/config.go | livekit/livekit_room.pb.go | pkg/config/base.go | SIP APIs | LiveKit Docsancient-iron-20196
09/19/2025, 12:00 PMtall-airline-16756
09/19/2025, 12:00 PMempty_timeout and `departure_timeout`: These settings help control how long a room stays active when no one is inside or after everyone leaves. You can easily adjust these in your LiveKit server configuration file.
2. Using Tokens with Time-to-Live (TTL): By generating access tokens that expire after a certain time, participants will be disconnected automatically once their token runs out. This is something you manage when creating tokens in your application.
3. Programmatically Deleting Rooms: You can also use the LiveKit Server API to delete a room after a set period. For instance, scheduling a task to call the deleteRoom API after a specific duration works well.
Feel free to let me know which option sounds best for you, and I’d be happy to walk you through the detailed steps to get it all set up!ancient-iron-20196
09/19/2025, 12:07 PMtall-airline-16756
09/19/2025, 12:07 PMdeleteRoom API: Once the desired time limit is reached (say, 5 minutes), you can use the LiveKit Server API to delete the room, which will gracefully disconnect all participants. Here’s an example using the Python SDK to get you started:
from livekit import api
import asyncio
async def delete_room_after_duration(room_name, duration):
await asyncio.sleep(duration) # Wait for the specified duration (in seconds)
api_client = api.LiveKitAPI(
"LIVEKIT_URL", # Replace with your LiveKit server URL
"LIVEKIT_API_KEY", # Replace with your API key
"LIVEKIT_API_SECRET" # Replace with your API secret
)
await api_client.room.delete_room(api.DeleteRoomRequest(
room=room_name
))
# Example: Delete a room named 'test-room' after 5 minutes (300 seconds)
asyncio.run(delete_room_after_duration("test-room", 300))
This method gives you the flexibility to enforce session limits tailored to your needs. If you’d like, I’m here to help you with the implementation or discuss any specific requirements you might have. Just let me know!ancient-iron-20196
09/19/2025, 12:10 PMtall-airline-16756
09/19/2025, 12:10 PMwith_ttl() method from the AccessToken class. Here's a friendly example to guide you through it:
from livekit.api import AccessToken
import datetime
token = AccessToken(api_key="LIVEKIT_API_KEY", api_secret="LIVEKIT_API_SECRET")
token.with_identity(identity)
token.with_metadata(metadata_token)
token.with_grants(api.VideoGrants(room_join=True, room=room))
# Set TTL to 5 minutes (300 seconds)
token.with_ttl(datetime.timedelta(minutes=5))
jwt_token = token.to_jwt()
This will create a token that expires 5 minutes after it’s issued. If you have any questions or need a hand with anything else, just let me know—I’m here to help!
Sources: livekit-api/tests/test_access_token.pyancient-iron-20196
09/19/2025, 12:54 PMtall-airline-16756
09/19/2025, 12:55 PMmax_endpointing_delay parameter in the AgentSession configuration. This sets the maximum time (in seconds) the system waits after detecting silence before it gently nudges a turn. Here's an example:
session = voice.AgentSession(
turn_detection=turn_detector.MultilingualModel(),
min_endpointing_delay=0.5, # Minimum delay after silence
max_endpointing_delay=6.0 # Maximum delay before forcing a turn
)
1. Force a Turn Manually: If you'd like, you can also programmatically force a turn using the commit_user_turn() method. Here's a quick snippet:
session.commit_user_turn(transcript_timeout=2.0)
1. Custom Inactivity Handling: Another friendly option is to implement a custom timeout that keeps track of user activity and gently prompts after some silence. For example:
class InactivityHandler:
def __init__(self, timeout_seconds=10, message="Are you still there?"):
self._timeout = timeout_seconds
self._message = message
async def _check_timeout(self):
while True:
await asyncio.sleep(1)
if time.time() - self._last_active > self._timeout:
await self._agent.say(self._message)
break
I’m here if you want to dive deeper or need any help setting these up—just let me know!
Sources: Turn detection and interruptions | LiveKit Docs | LiveKit turn detector plugin | LiveKit Docs | Improving voice AI's turn detection with transformers | AI voice agents | LiveKit Docs | Improving voice AI's turn detection with transformersancient-iron-20196
09/19/2025, 12:57 PMtall-airline-16756
09/19/2025, 12:58 PMuser_away_timeout to 15 seconds and use the @session.on("user_state_changed") event to have the agent respond with specific words. Here’s a friendly example to guide you through it:
async def entrypoint(ctx: JobContext):
session = AgentSession(
vad=silero.VAD.load(),
llm=openai.LLM(model="gpt-4o-mini"),
stt=deepgram.STT(),
tts=cartesia.TTS(),
user_away_timeout=15.0 # Set timeout to 15 seconds
)
@session.on("user_state_changed")
def _user_state_changed(ev: UserStateChangedEvent):
if ev.new_state == "away":
# Make the agent respond with specific words
asyncio.create_task(session.generate_reply(
instructions="Are you still there?"
))
await session.start(agent=Agent(instructions="You are a helpful assistant."), room=ctx.room)
So, with this setup, your agent will gently ask "Are you still there?" when it notices the user has been away for 15 seconds. If you have any questions or want to explore more, just let me know—I’m here to help!
Sources: livekit-agents/livekit/agents/voice/events.py | agent_extensions/README.mdancient-iron-20196
09/19/2025, 6:45 PMtall-airline-16756
09/19/2025, 6:46 PMuser_started_speaking event and update a timestamp each time the user talks.
2. Watch for Silence: Set up a background task that checks how long it’s been since the last time the user spoke. If it goes beyond your chosen limit, the call will disconnect.
import asyncio
import time
SILENCE_THRESHOLD = 5 # seconds
async def entrypoint(ctx: JobContext):
user_last_spoke_time = time.time()
async def monitor_interaction():
while True:
if time.time() - user_last_spoke_time > SILENCE_THRESHOLD:
await ctx.room.disconnect() # Disconnect the room
break
await asyncio.sleep(1)
@ctx.agent.on("user_started_speaking")
def on_user_started_speaking(_msg):
nonlocal user_last_spoke_time
user_last_spoke_time = time.time()
asyncio.create_task(monitor_interaction())
This method helps make sure the call ends smoothly if there’s been silence for too long. If you’d like, I’m here to help you with any part of this or answer any questions!
Sources: Improving voice AI's turn detection with transformers | Improving voice AI's turn detection with transformers | SIP APIs | LiveKit Docs | Speech & Audio Processing | livekit/livekit_composite | DeepWiki | agent_extensions/agent_extensions/handlers/inactivity_handler.pyancient-iron-20196
09/19/2025, 6:47 PMtall-airline-16756
09/19/2025, 6:47 PMuser_started_speaking event along with a monitoring task to keep track of silence duration.
If your scenario involves SIP calls, another option is to use the max_call_duration parameter to set a limit on the total call time, although this isn’t specifically tied to user inactivity.
Please feel free to reach out if you’d like some help implementing the custom solution or if you want to explore other possibilities together. I’m here to support you!ancient-iron-20196
09/19/2025, 6:56 PMtall-airline-16756
09/19/2025, 6:56 PMuser_started_speaking event and update a timestamp each time the user speaks. This way, we know exactly when they last interacted.
2. Monitor Silence: Run a background task that keeps an eye on how much time has passed since the user last spoke. If the silence goes beyond your set limit, the system will disconnect the room automatically.
Here’s a sample implementation to illustrate this:
import asyncio
import time
SILENCE_THRESHOLD = 10 # seconds
async def entrypoint(ctx: JobContext):
user_last_spoke_time = time.time()
async def monitor_interaction():
while True:
if time.time() - user_last_spoke_time > SILENCE_THRESHOLD:
await ctx.room.disconnect() # Disconnect the room
break
await asyncio.sleep(1)
@ctx.agent.on("user_started_speaking")
def on_user_started_speaking(_msg):
nonlocal user_last_spoke_time
user_last_spoke_time = time.time()
asyncio.create_task(monitor_interaction())
This way, the call will gracefully end if the user stays silent for longer than the time you specify. If you’d like, I’m here to help you customize this further to fit your exact needs—just let me know!ancient-iron-20196
09/19/2025, 6:58 PMtall-airline-16756
09/19/2025, 6:58 PMuser_started_speaking event, which helps cut down on unnecessary checks.
• Clean Up Tasks: Don’t forget to properly cancel or clean up the polling task when the session ends—this helps prevent any memory leaks down the road.
Another option is to use asynchronous tools like asyncio.wait_for or event-based handlers to get the same result without constant polling. If you’d like, I’d be more than happy to share an example of how that works!ancient-iron-20196
09/19/2025, 7:00 PMtall-airline-16756
09/19/2025, 7:00 PMasyncio.wait_for to handle user inactivity without the need for continuous polling:
import asyncio
import time
SILENCE_THRESHOLD = 10 # seconds
async def entrypoint(ctx: JobContext):
user_last_spoke_event = asyncio.Event()
async def monitor_inactivity():
while True:
try:
# Wait for the user to speak within the threshold
await asyncio.wait_for(user_last_spoke_event.wait(), timeout=SILENCE_THRESHOLD)
user_last_spoke_event.clear() # Reset the event after user speaks
except asyncio.TimeoutError:
# Silence threshold exceeded, disconnect the room
await ctx.room.disconnect()
break
@ctx.agent.on("user_started_speaking")
def on_user_started_speaking(_msg):
user_last_spoke_event.set() # Signal that the user has spoken
asyncio.create_task(monitor_inactivity())
This method helps us avoid constant polling by patiently waiting for either user activity or a timeout. It’s a neat and efficient way to ensure the room disconnects only when the silence threshold is truly exceeded. If you’d like me to walk you through any part of this or if you have more questions, please don’t hesitate to ask—I’m here to help!ancient-iron-20196
09/19/2025, 7:11 PMtall-airline-16756
09/19/2025, 7:12 PMpip install "livekit-agents[resemble]~=1.2"
2. Authenticate: You’ll need to provide your Resemble AI API key and voice_uuid (which identifies the voice) either as environment variables or directly in your code.
3. Use the Plugin: Here’s a quick example for one-off synthesis:
from livekit.plugins import resemble
import asyncio
async def main():
tts = resemble.TTS(
api_key="your_api_key",
voice_uuid="your_voice_uuid",
sample_rate=44100,
output_format="wav"
)
audio_stream = tts.synthesize("Hello, world!")
async for chunk in audio_stream:
print(f"Received audio chunk: {len(chunk.frame.data)} bytes")
asyncio.run(main())
If you’d like, I’m here to help you set up real-time streaming or explore any other customizations you have in mind. Just let me know!
Sources: Resemble AI TTS integration guide | LiveKit Docs | livekit-plugins/livekit-plugins-resemble/livekit/plugins/resemble/py.typed | plugins/resemble/src/tts.test.ts | Resemble AI TTS integration guide | LiveKit Docsancient-iron-20196
09/19/2025, 7:13 PMtall-airline-16756
09/19/2025, 7:14 PMancient-iron-20196
09/19/2025, 7:22 PMtall-airline-16756
09/19/2025, 7:23 PMtts.TTS base class and implement the stream() method for real-time synthesis or synthesize() if you prefer non-streaming output.
2. Integrate Your TTS Engine: Consider using open-source options like Coqui TTS or MaryTTS. You can send your text input to the engine and then convert the generated audio into AudioFrame objects using LiveKit’s AudioByteStream.
3. Configure in AgentSession: Finally, add your custom TTS class to the AgentSession configuration, so it’s enabled within your LiveKit application.
Here’s a quick example to illustrate:
class CustomTTSEngine(tts.TTS):
def __init__(self, model, sample_rate, num_channels):
super().__init__(streaming=True, sample_rate=sample_rate, num_channels=num_channels)
self._model = model
async def stream(self):
# Implement streaming logic here
pass
This method lets you bring in any open-source TTS engine smoothly. If you’d like, I’m here to provide more detailed steps for a specific TTS engine you have in mind—just let me know!
Sources: Text-to-speech (TTS) integrations | LiveKit Docs | plugins/elevenlabs/src/tts.ts | OpenAI Realtime API integration guide | LiveKit Docs