Hi team. I've been working on Livekit since the past 3 months now and one error keeps on popping up throughout off and on. Sharing below: ERROR livekit.agents - Error in _realtime_reply_task ERROR asyncio - Task exception was never retrieved future: <Task finished name='AgentActivity.realtime_reply' coro=<AgentActivity._realtime_reply_task() done, defined at /Users/mac/Documents/convo-agent/.venv/lib/python3.9/site-packages/livekit/agents/utils/log.py:13> exception=RealtimeError('generate_reply timed out.')> WARNING livekit.plugins.openai - response received after timeout {"response_id": "resp_Bwuet4kskIfJVGJdYB63W", "pid": 6981, "job_id": "AJ_hEJhqDCviKvZ"} This is the exact order in which this error occurs. When this happens: the agent goes silent. I've tried a bunch load of options however this still pops up off and on. If anyone can give me any direction that would be very helpful. Can't role the agent out for production till i dont have confidence that this behvior will stop Im unsure on whats causing this. I have some function_tools which return instructions for the agent to follow and a generate_reply in the entry point

Thanks for reaching out, Ahmed. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

Can you tell me how I can do option 2 3 and 5

Hey there! Let me walk you through some friendly tips on making your LiveKit experience super smooth and reliable. Think of this like having a tech buddy helping you out! 1. Implement Retry Logic LiveKit's got your back with some smart retry features. Here's how you can make them work for you: • Session Restart with Exponential Backoff: Imagine this like a smart waiting game. If something goes wrong, you'll wait a bit longer each time before trying again. The formula is

delay = 2 ** (session_restart_attempts - 1) - 1

. Just be sure to set a max retry limit so you don't keep trying forever! • Connection-Level Retries: If an API error pops up, check if it's something you can retry and you haven't already tried too many times. 2. Manage Session Lifecycle Think of this like taking care of your app's health: • Session State Tracking: Use flags like

_is_sess_active

to keep an eye on your session and handle shutdowns gracefully. • Reconnection and Recovery: When you reconnect, don't forget to bring back your important stuff - configuration events, tool updates, chat context. It's like picking up right where you left off! • Session Duration Management: Set up some automatic reconnection limits to keep things running smoothly over time. 3. Monitor Error Events Let's be proactive about catching potential issues: • Error Event Structure: Use the

ErrorEvent

from

AgentSession

to keep tabs on what might be going wrong. It'll tell you if the error is something you can fix or if you need to step in. • Error Classification: Some errors you can bounce back from, others might need a bit more attention. Know the difference! • Fallback Mechanisms: The

FallbackAdapter

is like having a backup plan - if one provider fails, it'll automatically switch to another. Pretty cool, right? By using these strategies, you'll create an app that's resilient, reliable, and ready to handle whatever comes its way. You've got this! Sources: livekit-agents/livekit/agents/llm/llm.py | Events and error handling | LiveKit Docs

how do I ensure that a session ended gracefully, and how do I restart a session if a timeout occurs

Hey there! Let me walk you through a super helpful way to manage your sessions smoothly and handle those pesky timeouts like a pro. 1. Ensuring Graceful Session Ending • For Agent Sessions: Think of the

shutdown

method as your friendly goodbye button. Here's how you can use it:

async def entrypoint(ctx: JobContext):
    # Perform necessary tasks
    ...
    # Disconnect from the room
    ctx.shutdown(reason="Session ended")

• For Realtime Model Sessions: The

aclose()

method is your go-to for tidying up. Check out this example:

async def aclose(self) -> None:
    <http://logger.info|logger.info>("Attempting to shutdown agent session")
    if not self._is_sess_active.is_set():
        <http://logger.info|logger.info>("Agent session already inactive")
        return

    for event in self._event_builder.create_prompt_end_block():
        await self._send_raw_event(event)
    self._is_sess_active.clear()

    if self._stream_response and not self._stream_response.output_stream.closed:
        await self._stream_response.output_stream.close()

• This approach makes sure everything gets wrapped up nicely – no loose ends! 2. Restarting a Session After Timeout • Automatic Session Restart: We've got a smart way to restart sessions with a built-in retry mechanism. Take a look:

async def _restart_session(self, ex: Exception) -> None:
    if self._session_restart_attempts >= DEFAULT_MAX_SESSION_RESTART_ATTEMPTS:
        logger.error("Max session restart attempts reached, exiting")
        return

    self._session_restart_attempts += 1
    self._is_sess_active.clear()
    delay = 2 ** (self._session_restart_attempts - 1) - 1
    await asyncio.sleep(min(delay, DEFAULT_MAX_SESSION_RESTART_DELAY))
    await self.initialize_streams(is_restart=True)
    <http://logger.info|logger.info>(f"Session restarted successfully ({self._session_restart_attempts}/{DEFAULT_MAX_SESSION_RESTART_ATTEMPTS})")

• Timeout Detection and Recovery: Here's how you can catch those timeout moments and bounce back:

except ModelTimeoutException as mte:
    logger.warning(f"Model timeout error: {mte}\nAttempting to recover...")
    await self._restart_session(mte)

• Connection Pool Management: Pro tip: Use connection pools that can automatically manage session lifetimes for you! With these friendly tips, you'll be handling sessions like a total champ – smooth sailing all the way! Sources: Job lifecycle | LiveKit Docs | livekit-agents/livekit/agents/utils/connection_pool.py | livekit/src/rtc_engine/rtc_session.rs

Lets stick to Ensuring Graceful Session Ending first I have a @ctx.room.on("participant_disconnected"). In this i wrap up the session. So based on your instructions, I would first do ctx.shutdown(reason="Session ended") then logger.info("Attempting to shutdown agent session") if not self._is_sess_active.is_set(): logger.info("Agent session already inactive") return for event in self._event_builder.create_prompt_end_block(): await self._send_raw_event(event) self._is_sess_active.clear() if self._stream_response and not self._stream_response.output_stream.closed: await self._stream_response.output_stream.close() or do I just declare the aclose function separately. Can you give me a sample example of how I would do this?

Hey there! Let me walk you through a super helpful way to smoothly end your LiveKit agent sessions. Think of this like having a thoughtful exit strategy that takes care of all the little details. 😊

import asyncio
from livekit.agents import JobContext, AgentSession

async def entrypoint(ctx: JobContext):
    session: AgentSession | None = None

    try:
        # Create and start the agent session
        session = AgentSession(...)

        # Register shutdown callback for graceful cleanup
        async def shutdown_handler(reason: str):
            print(f"Shutdown initiated: {reason}")
            if session:
                # Gracefully close the agent session
                await session.aclose()

        ctx.add_shutdown_callback(shutdown_handler)

        # Connect to the room
        await ctx.connect()

        # Start the agent session
        await session.start(agent=MyAgent(), room=ctx.room)

        # Set up session close event handler
        @session.on("close")
        def on_session_close(ev):
            print(f"Session closed: {ev.reason}")
            # Trigger context shutdown after session closes
            ctx.shutdown(reason="Session completed")

        # Wait for participants or shutdown signal
        shutdown_future: asyncio.Future[None] = asyncio.Future()

        async def on_shutdown_signal(reason: str):
            if not shutdown_future.done():
                shutdown_future.set_result(None)

        ctx.add_shutdown_callback(on_shutdown_signal)

        # Monitor for room empty condition
        room_empty_future: asyncio.Future[None] = asyncio.Future()

        def on_participant_disconnected(_):
            if len(ctx.room.remote_participants) == 0 and not room_empty_future.done():
                room_empty_future.set_result(None)

        ctx.room.on("participant_disconnected", on_participant_disconnected)

        try:
            # Wait for either shutdown signal or room to become empty
            await asyncio.wait(
                [shutdown_future, room_empty_future], 
                return_when=asyncio.FIRST_COMPLETED
            )
        finally:
            # Clean up event handlers
            ctx.room.off("participant_disconnected", on_participant_disconnected)

            # Ensure session is closed gracefully
            if session:
                await session.aclose()
                session = None

    except Exception as e:
        print(f"Error in entrypoint: {e}")
        # Trigger shutdown on error
        ctx.shutdown(reason=f"Error: {str(e)}")

    finally:
        # Final cleanup - ensure session is closed
        if session:
            await session.aclose()

class MyAgent:
    def __init__(self):
        self.instructions = "You are a helpful assistant."

    async def close_session_gracefully(self, session: AgentSession):
        """Example method to close session from within agent logic"""
        await session.generate_reply(instructions="Say goodbye to the user")
        await session.aclose()

if __name__ == "__main__":
    cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))

Key Points: • Use

ctx.add_shutdown_callback()

to register cleanup functions. • Call

await session.aclose()

to ensure all resources are released properly. • Handle session close events to trigger context shutdown when necessary. • Ensure cleanup happens even in error scenarios by using

try-finally

blocks. I know this might look a bit complex, but trust me, it's like having a really reliable friend who makes sure everything gets wrapped up neatly. By following these steps, you'll prevent any messy resource leaks and keep your agent sessions running smoothly. Pretty cool, right? 👍 Sources: Inside a session | LiveKit Docs | livekit-agents/livekit/agents/voice/room_io/room_io.py

now for Restarting a Session After Timeout can you give me an example of how to catch a timeout and then initiate a restart

Hey there! Let me walk you through a friendly way to handle timeouts and restart your LiveKit session. Think of it like having a backup plan when things get a bit wonky.

async def _process_responses(self):
    """Main response processing loop with timeout handling and session restart."""
    try:
        while self._is_sess_active.is_set():
            try:
                # Process responses from the stream
                result = await self._stream_response.get_next_event()

                if result.value and result.value.bytes_:
                    response_data = result.value.bytes_.decode("utf-8")
                    json_data = json.loads(response_data)
                    await self._handle_event(json_data)

            except ModelTimeoutException as mte:
                logger.warning(f"Model timeout error: {mte}\nAttempting to recover...")
                await self._restart_session(mte)
                break

            except (ThrottlingException, ModelNotReadyException, ModelErrorException) as re:
                logger.warning(f"Retryable error: {re}\nAttempting to recover...")
                await self._restart_session(re)
                break

    except Exception as e:
        logger.error(f"Response processing error: {e}")
        raise

async def _restart_session(self, ex: Exception) -> None:
    """Restart the session with exponential backoff."""
    if self._session_restart_attempts >= DEFAULT_MAX_SESSION_RESTART_ATTEMPTS:
        logger.error("Max session restart attempts reached, exiting")
        self._emit_error(ex, recoverable=False)
        self._is_sess_active.clear()
        return

    self._session_restart_attempts += 1
    self._is_sess_active.clear()

    # Exponential backoff delay
    delay = 2 ** (self._session_restart_attempts - 1) - 1
    await asyncio.sleep(min(delay, DEFAULT_MAX_SESSION_RESTART_DELAY))

    # Reinitialize the streams
    await self.initialize_streams(is_restart=True)

    <http://logger.info|logger.info>(
        f"Session restarted successfully ({self._session_restart_attempts}/{DEFAULT_MAX_SESSION_RESTART_ATTEMPTS})"
    )

Here's the breakdown: • Timeout Detection: Keep an eye out for those tricky timeout exceptions like

ModelTimeoutException

. • Exponential Backoff: Give your service a little breathing room between restart attempts. It's like a gentle "let's try again" approach with

delay = 2 ** (self._session_restart_attempts - 1) - 1

. • Attempt Limiting: We don't want to keep hammering away forever, so we set a max retry limit. • Session State Management: Clean up and reset before making another go of it. • Graceful Recovery: Smoothly reinitialize those streams after a short pause. This approach is like having a trusty safety net – keeping things running smoothly even when unexpected hiccups pop up! Sources: livekit-plugins/livekit-plugins-google/livekit/plugins/google/beta/realtime...

is there a way to simulate a timeout error for testing purposes?

Hey there! Let me walk you through some cool ways to simulate timeout errors in LiveKit for testing. It's super helpful to know how your app handles those tricky timeout situations. 1. Using Fake/Mock Components • For TTS/STT Testing (Python): LiveKit's test utilities are your friend here! Check out how you can create a fake TTS that simulates timeouts:

from tests.fake_tts import FakeTTS

# Create a fake TTS with timeout simulation
fake_tts = FakeTTS(fake_timeout=5.0)  # 5 second timeout

# The fake implementation will sleep for the timeout duration
# and raise APIConnectionError if timeout exceeds conn_options.timeout

2. Using Toxiproxy for Network-Level Timeouts • Want to mimic real-world network hiccups? Toxiproxy lets you inject timeout toxics into network connections. Pretty neat, right?

# Set up toxiproxy with timeout toxic
p = toxiproxy.create(proxy_upstream, proxy_name, listen=PROXY_LISTEN, enabled=True)
p.add_toxic(type="timeout", attributes={"timeout": 0})

# Test timeout behavior
with pytest.raises(APITimeoutError):
    await asyncio.wait_for(
        _do_synthesis(
            tts_v,
            TEST_AUDIO_SYNTHESIZE,
            conn_options=APIConnectOptions(max_retry=0, timeout=2.5),
        ),
        timeout=10,
    )

3. RPC Timeout Simulation • JavaScript/TypeScript: Here's a quick way to test those timeout scenarios:

const timeout = 50;
const resultPromise = localParticipant.performRpc({
  destinationIdentity: mockRemoteParticipant.identity,
  method: 'timeoutMethod',
  payload: 'timeoutPayload',
  responseTimeout: timeout,
});

// Simulate delay longer than timeout
mockSendDataPacket.mockImplementationOnce(() => {
  return new Promise((resolve) => {
    setTimeout(resolve, timeout + 10);
  });
});

await expect(resultPromise).rejects.toThrow('Response timeout');

4. Flutter/Dart: Testing timeout responses can be a breeze with this approach:

room.registerRpcMethod('echo', (RpcInvocationData data) async {
  await Future.delayed(Duration(seconds: 10));  // Longer than timeout
  return 'echo: => ${data.callerIdentity} ${data.payload}';
});

try {
  await room.localParticipant?.performRpc(PerformRpcParams(
    destinationIdentity: room.localParticipant!.identity,
    method: 'echo',
    payload: 'hello',
    responseTimeoutMs: Duration(seconds: 2),  // Shorter timeout
  ));
} catch (e) {
  if (e is RpcError) {
    expect(RpcError.responseTimeout, e.code);
  }
}

Now you've got a toolkit to test all sorts of timeout scenarios across different LiveKit components! Whether it's connection timeouts, response delays, or API hiccups, you'll be prepared. Happy testing! 😊 Sources: src/room/rpc.test.ts | test/core/rpc_test.dart | livekit-android-sdk/src/main/java/io/livekit/android/room/Room.kt | pkg/testutils/timeout.go | tests/fake_stt.py

Can I implement a Fallback adapter using llm=openai.realtime.RealtimeModel( voice="alloy" ),

I don't have the answer you're looking for. You could also try asking your question: • in one of the other Slack channels or • to https://deepwiki.com/livekit/livekit_composite which is trained on all LiveKit source code If you find the answer, please post it here to help others!