i have a Python client connected to a room and an agent connects on manual dispatch. i want to leverage and configurate everything on both client and agent to send a preconnect buffer so i don't miss any of the audio users speaks while agent connecting to the room

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

i want help from the Python client side mainly

Thank you for reaching out! I wanted to share that the LiveKit Python client doesn’t currently support direct configuration of a preconnect audio buffer. This feature is available in other SDKs like Swift, Android, and JS, where audio can be buffered before the room connection is fully established and then sent to an agent upon connection. On the Python side, the focus is usually on the agent’s server-side processing, where the

PreConnectAudioHandler

helps receive and process buffered audio sent from other clients. If your goal is to buffer audio on the client side before the agent connects, you might want to explore one of the supported SDKs like Swift, Android, or JS. Please feel free to reach out if you’d like any clarification or help exploring other options—I’m here to assist you! Sources: livekit/livekit_models.pb.go | livekit-ffi/protocol/track.proto | livekit-agents/livekit/agents/voice/room_io/_input.py | README.md | livekit-protocol/livekit/protocol/models.pyi

does the preconnect audio get recorded on the RoomEgress recorder?

I wanted to share a little insight about the preconnect audio buffer and RoomEgress recordings. The preconnect audio buffer isn’t recorded in RoomEgress because it’s sent as a byte stream under the topic

lk.agent.pre-connect-audio-buffer

, rather than being published as a standard media track within the room. RoomEgress recordings focus on capturing audio and video tracks that are published during the room session once participants have joined. Since the preconnect buffer works separately from these media tracks, it doesn’t get included in the RoomEgress output. If you have any questions or need me to explain anything further, please don’t hesitate to ask—I’m here to help! Sources: livekit-rtc/livekit/rtc/_proto/track_pb2.pyi | livekit-android-sdk/src/main/java/io/livekit/android/audio/PreconnectAudioB... | src/room/track/options.ts | Session recording and transcripts | LiveKit Docs | livekit-agents/livekit/agents/voice/room_io/_pre_connect_audio.py

i had to add a small delay on the client because the pre-connect buffer wasn't being received before the stream handler was registered on the agent, is there a better way to handle that?

Let's work together to smoothly handle timing issues with the pre-connect audio buffer and make sure it’s received before the stream handler is registered on the agent. Here are some friendly best practices to guide you: 1. Start Buffering Early: Try to initiate the pre-connect audio buffer before the room connection starts. This helps prevent those tricky race conditions where audio might be spoken too soon and gets lost. 2. Synchronize Timeout Values: The default timeout for pre-connect audio on the client side is 10 seconds. On the agent side, it’s a good idea to set the

pre_connect_audio_timeout

in

RoomInputOptions

to match or be a bit longer than this. For example:`room_io = RoomIO( agent_session, room, input_options=RoomInputOptions( pre_connect_audio=True, pre_connect_audio_timeout=10.0 # Match client timeout ) )` 3. Register the Handler Before Connection: Make sure the

PreConnectAudioHandler

is registered before you call

ctx.connect()

. Here’s a quick example:`self._pre_connect_audio_handler = PreConnectAudioHandler( room=self._room, timeout=self._input_options.pre_connect_audio_timeout, ) self._pre_connect_audio_handler.register() # Call before ctx.connect()` 4. Monitor Logs: Keep an eye out for warnings like "pre-connect audio buffer is too old" or "pre-connect audio received but not completed in time." These messages can really help pinpoint timing issues so you can address them quickly. 5. Process Audio Promptly: Encourage the agent to process the buffer quickly when starting up. This helps avoid losing valid data because of delays. Following these steps should help you avoid adding delays on the client side. If you have any questions or want to dive deeper into any part, I’m here to help—just let me know! Sources: Tests/LiveKitTests/PreConnectAudioBufferTests.swift | livekit-agents/livekit/agents/voice/room_io/room_io.py | CHANGELOG.md

i'm seeing the pre-connect audio received but sometimes it's not generating an openai response

Thanks so much for reaching out! To better understand and help you with the issue, could you please clarify a few things for me? • Are you seeing any specific error messages when using pre-connect audio with OpenAI? • Is the problem that you’re not getting any response at all, or that the response comes through as text-only when you were expecting audio? • Also, are you loading conversation history when this happens? Knowing these details will really help us get to the bottom of this and find the best solution for you. Looking forward to your reply! Sources: livekit-plugins/livekit-plugins-openai/livekit/plugins/openai/realtime/real... | plugins/openai/src/realtime/api_proto.ts | OpenAI Realtime API integration guide | LiveKit Docs | OpenAI Realtime API integration guide | LiveKit Docs | Azure OpenAI Realtime API and LiveKit | LiveKit Docs

• no error • no response at all • no, it's a fresh session

I'm here to help you troubleshoot the situation where pre-connect audio is received but doesn’t generate an OpenAI response. Let’s walk through some steps together to get this sorted out: 1. Verify RoomIO Configuration: Please make sure that

pre_connect_audio=True

is set in the

RoomInputOptions

during initialization. For example:`room_io = RoomIO( agent_session=agent_session, room=room, input_options=RoomInputOptions( pre_connect_audio=True, pre_connect_audio_timeout=3.0, ), )` 2. Ensure Proper Handler Registration: It’s important that the

PreConnectAudioHandler

is registered before the room connects. Be sure to call

room_io.start()

before

ctx.room.connect()

. 3. Check Timeout Settings: The default timeout for pre-connect audio is 3 seconds. Make sure the client sends audio promptly and the server processes it within this timeframe. If needed, you can increase the timeout. 4. Inspect WebSocket Events: Keep an eye on events like

input_audio_buffer.speech_started

and

response.audio.done

to confirm that audio is being received and processed. Enabling debug logging with

LK_OPENAI_DEBUG=1

can really help you trace these events. 5. Validate Audio Format: Double-check that the pre-connect audio is in PCM16, 24kHz, mono format. Sometimes, if the input is malformed, it might not process correctly. 6. Check OpenAI Realtime API Configuration: Confirm that the

RealtimeModel

is set with

modalities=['text', 'audio']

so it can generate audio responses. I hope these steps help you identify and resolve the issue. If you run into any trouble or have more questions, please don’t hesitate to reach out—I’m here to support you! Sources: plugins/openai/src/realtime/api_proto.ts | tests/test_tts.py | Sources/LiveKit/Core/Room+PreConnect.swift | OpenAI Realtime API integration guide | LiveKit Docs

i'm not using RoomIO, im using AgentSession with RoomInputOptions

Let's work together to troubleshoot the pre-connect audio issues you're experiencing with

AgentSession

and

RoomInputOptions

. Here are some friendly steps to guide you: 1. Enable Pre-Connect Audio: First, please make sure that

pre_connect_audio=True

is set in

RoomInputOptions

. For example:`input_options = RoomInputOptions(pre_connect_audio=True)` 2. Adjust Timeout: The default timeout is 3 seconds, but if you find it’s not enough, you can increase it like this:`input_options = RoomInputOptions( pre_connect_audio=True, pre_connect_audio_timeout=5.0 # Extend to 5 seconds )` 3. Verify Metadata: It’s important that the client sends the byte stream under the correct topic (

lk.agent.pre-connect-audio-buffer

) and includes metadata such as

sampleRate

,

channels

, and

trackId

. This helps everything run smoothly. 4. Check Audio Format: The handler supports Opus-encoded or raw PCM audio. Please double-check that the MIME type and encoding are exactly as expected. 5. Monitor Logs: Turning on debug logs can be really helpful! Look out for messages like

"pre-connect audio received"

or

"timeout waiting for pre-connect audio buffer"

. These clues can show us where the issue might be. 6. Participant Setup: Lastly, make sure your

AgentSession

is set up correctly to receive pre-connect audio, and if needed, use

participant_identity

in

RoomInputOptions

. If any of these steps feel unclear or if you’d like a hand with anything else, please don’t hesitate to reach out. I’m here to help! Sources: examples/voice_agents/realtime_joke_teller.py | Community & Support | livekit/livekit_composite | DeepWiki

i got this debug message:

OpenAI Realtime API response done but not complete with status: cancelled

I'm here to help you understand the error

OpenAI Realtime API response done but not complete with status: cancelled

. This message means the response was stopped before it could finish, which can happen for a couple of reasons: • Turn Detection: The server’s voice activity detection (VAD) noticed user speech and automatically paused the response. • Manual Cancellation: The response was intentionally cancelled using the

response.cancel

event, often triggered by the

interrupt()

method in the LiveKit OpenAI plugin. Here’s how you can handle this: • If it’s due to turn detection, this is normal during conversations. Just make sure your app switches to listening mode when this happens. • If it’s a manual cancellation, take a moment to check your application’s logic to see if this was on purpose or if you might want to tweak it. Please don’t hesitate to reach out if you’d like me to walk you through any part of this or if you have more questions. I’m happy to assist! Sources: agents/src/metrics/base.ts | livekit-plugins/livekit-plugins-aws/livekit/plugins/aws/experimental/realti...

i see a response.cancel event sent but i don't know where it come from

I'm glad you asked about the

response.cancel

event in LiveKit's OpenAI integration! This event can happen in a couple of ways: 1. Manual Interruption: This is when the

interrupt()

method is called on the

RealtimeSession

. It sends a

response.cancel

event to gracefully stop the assistant’s current response. 2. Automatic Interruption: If you have server-side turn detection enabled (like with

interrupt_response: true

), the event triggers when voice activity detection (VAD) senses the user speaking, indicating they want to interrupt the assistant. To figure out what’s causing the event, you can check your app’s logic for any

interrupt()

calls or take a look at your session’s turn detection settings. If you’d like, I’m here to help you dig deeper and get everything running smoothly! Sources: plugins/openai/src/realtime/realtime_model.ts | livekit-plugins/livekit-plugins-openai/livekit/plugins/openai/realtime/real...

the preconnect buffer is getting interrupted by vad i think, which is wrong

Let's make sure your Voice Activity Detection (VAD) doesn't interrupt the pre-connect audio buffer. Here’s a friendly step-by-step guide to help you through it: 1. Ensure Proper Client-Side Buffering: Try using the

withPreconnectAudio

helper (or something similar) in the client SDK. This helps keep the pre-connect audio buffer separate from the real-time audio stream where VAD works, so it won’t get interrupted. 2. Initialize RoomIO Before Connection: On the agent side, it’s best to call

room_io.start()

before

ctx.connect()

. Doing this early registers the pre-connect audio handler and lets it handle the buffer before real-time audio kicks in. 3. Disable Server VAD (Optional): If you’d prefer full control, you can disable server-side VAD by setting

turn_detection=None

in the OpenAI Realtime API configuration. This way, automatic interruptions won’t happen, and you can manage responses manually. 4. Trust Built-In Sequencing: The LiveKit framework is designed to process the pre-connect buffer first, delivering it to the agent before starting real-time audio and VAD. Just make sure your initialization follows this order. Following these steps should help keep your pre-connect audio buffer safe from VAD interruptions. If anything’s unclear or you want a bit more help, just let me know—I’m here for you! Sources: livekit-plugins/livekit-plugins-silero/livekit/plugins/silero/vad.py | Voice activity detection (VAD) parameters | LiveKit Docs | livekit-android-sdk/src/main/java/io/livekit/android/audio/PreconnectAudioB... | Sources/LiveKit/Core/Room+PreConnect.swift

i want to use VAD but without interrupting ongoing responses

To help you configure VAD in LiveKit and avoid interruptions during ongoing responses, here are some friendly steps you can follow: 1. Adjust VAD Sensitivity: Try increasing

min_silence_duration

to at least 600ms. This helps prevent the system from mistakenly thinking the turn has ended too soon. For example:`vad = silero.VAD.load( min_silence_duration=0.6, # Prevents interruptions during pauses activation_threshold=0.6 )` 2. Set Endpointing Delays: You can configure

min_endpointing_delay

and

max_endpointing_delay

in

AgentSession

to give the system more time before deciding a turn is finished:`session = AgentSession( min_endpointing_delay=1.0, # Wait at least 1s after silence max_endpointing_delay=6.0 # Wait up to 6s for low-confidence turns )` 3. Enable False Interruption Recovery: This setting allows the agent to resume speaking if it was interrupted by mistake, which can be really helpful:`session = AgentSession( false_interruption_timeout=1.0, # Wait 1s after interruption resume_false_interruption=True # Resume if no new input )` 4. Fine-Tune Turn Detection: If you’re using OpenAI Realtime, adjusting

silence_duration_ms

and

threshold

in the turn detection settings can improve accuracy:`session = AgentSession( llm=realtime.RealtimeModel( turn_detection=TurnDetection( type="server_vad", silence_duration_ms=800, # Increase silence threshold threshold=0.6 ) ) )` 5. Use Semantic Turn Detection: Consider integrating the Turn Detector plugin for more precise end-of-turn predictions based on the flow of conversation. 6. Control Interruptions: To make sure the agent finishes its response without interruptions, set

allow_interruptions=False

like this:`session = AgentSession( allow_interruptions=False, min_interruption_duration=0.6 )` These tweaks should really help keep the conversation smooth and minimize any unwanted interruptions. If you have any questions or want to dive deeper into any of these steps, just let me know — I’m here to help! Sources: OpenAI Realtime API integration guide | LiveKit Docs | AI voice agents | LiveKit Docs | Improving voice AI's turn detection with transformers | How does end-of-utterance detection work in conversations? | basics/echo_transcriber_agent.py

definitely the pre-connect buffer is getting interrupted by the user audio once fully connected:

2025-09-13 23:25:08,039 - INFO events - User state changed from: listening to speaking
2025-09-13 23:25:08,039 - DEBUG livekit.plugins.openai - >>> {'type': 'response.cancel'}

but the User state should be Speaking when sending pre-connect audio

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!