hi

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

does openai realtime model support push-to-talk configuration? we struggled to do this with the gemini flash native live api

Thanks — I understand you’re asking whether the OpenAI Realtime model supports push-to-talk (you had trouble doing this with Gemini Flash native live API). Yes — OpenAI Realtime can be used in a push-to-talk style when integrated through LiveKit’s AgentSession by using manual turn detection. What you do is: • Start with audio input disabled:

session.input.set_audio_enabled(False)

• When the user presses the talk button, enable audio:

session.input.set_audio_enabled(True)

• When they release (end their turn), call

session.commit_user_turn()

so the agent processes the captured audio • If the user cancels, call

session.clear_user_turn()

to discard the audio instead • You can also call

session.interrupt()

any time to interrupt the agent, and control whether the agent’s speech can be interrupted using

allow_interruptions

on `say()`/`generate_reply()` This is supported in both Python and Node.js. For a complete example, see the Push-to-Talk Agent sample: https://github.com/livekit/agents/blob/main/examples/voice_agents/push_to_talk.py Would you like a short code snippet for your platform (Web/Android/iOS/Python/Node) showing the button handling and these calls? Sources: Turns overview | LiveKit docs

are you sure this approach works for realtime pipelines? or is it just for stt/llm/tts pipeliens

You're right to double-check — push-to-talk with manual turn detection works with realtime pipelines, not just STT/LLM/TTS pipelines. Key points: • Set

turn_detection="manual"

on the

AgentSession

. Turn control is handled at the session layer, not by the model. • Use

session.input.set_audio_enabled(False)

initially, enable it on button press, disable on release, then call

session.commit_user_turn()

to process the audio (or

session.clear_user_turn()

to discard). • This pattern works the same whether the session uses a realtime model (e.g., OpenAI Realtime) or a separate STT→LLM→TTS pipeline. Would you like a brief code snippet for your platform (Web/Android/iOS/Python/Node) showing the button handling and calls? Sources: Turns overview | LiveKit docs | Realtime model plugins | LiveKit Docs | OpenAI Realtime API plugin guide | LiveKit docs

how would i configure the openai realtime model agent session to do push to talk in python

Thanks — responding to your request for a Python example that configures an OpenAI Realtime model in an AgentSession for push-to-talk. Below is a concise, ready-to-run pattern you can use. It sets

turn_detection="manual"

, disables audio by default, and exposes RPC methods the frontend can call for start/end/cancel talk.

import asyncio
from dotenv import load_dotenv
from livekit import agents, rtc
from livekit.agents import AgentSession, AgentServer, JobContext, cli
from livekit.plugins import openai

load_dotenv()

server = AgentServer()

@server.rtc_session()
async def entrypoint(ctx: JobContext):
    # Realtime model + manual turn control for push-to-talk
    session = AgentSession(
        llm=openai.realtime.RealtimeModel(
            voice="alloy",
            temperature=0.8,
            modalities=["text", "audio"],
        ),
        turn_detection="manual",
    )

    await session.start(room=ctx.room)

    # Start with mic off (push-to-talk inactive)
    session.input.set_audio_enabled(False)

    # RPC called by frontend when user presses the talk button
    @ctx.room.local_participant.register_rpc_method("start_talk")
    async def start_talk(data: rtc.RpcInvocationData):
        session.interrupt()         # stop any agent speech
        session.clear_user_turn()   # clear previous staged input
        session.input.set_audio_enabled(True)  # start capturing audio
        return "ok"

    # RPC called when user releases the talk button
    @ctx.room.local_participant.register_rpc_method("end_talk")
    async def end_talk(data: rtc.RpcInvocationData):
        session.input.set_audio_enabled(False)  # stop capturing
        session.commit_user_turn()               # process & generate reply
        return "ok"

    # RPC to cancel current input (e.g., user aborted)
    @ctx.room.local_participant.register_rpc_method("cancel_talk")
    async def cancel_talk(data: rtc.RpcInvocationData):
        session.input.set_audio_enabled(False)
        session.clear_user_turn()
        return "ok"

if __name__ == "__main__":
    cli.run_app(server)

Frontend behavior (example): • On button down: call RPC

start_talk

. • On button up: call RPC

end_talk

. • If the user cancels mid-press: call

cancel_talk

. If you want, I can: • Provide a minimal web frontend example showing the RPC calls, or • Show a variant that allows interrupting the agent during its speech (using

allow_interruptions

). Which would help you more? Sources: Turns overview | LiveKit docs | OpenAI Realtime API plugin guide | LiveKit docs | Realtime model plugins | LiveKit Docs

do i need to do anything on the ios side regarding this? or is everything managed from the agent session?

You're all set — most push-to-talk work is managed by the AgentSession. On iOS you only need to: • Ensure microphone permission and that the participant publishes an audio track. • Call the backend RPCs you exposed for PTT (e.g.,

start_talk

,

end_talk

,

cancel_talk

) when the user presses/releases/cancels the button. • Subscribe to the agent's audio output so the user can hear replies. Minimal Swift example to call the RPCs:

// on button down
try await localParticipant.performRpc(method: "start_talk", payload: nil)

// on button up
try await localParticipant.performRpc(method: "end_talk", payload: nil)

// to cancel
try await localParticipant.performRpc(method: "cancel_talk", payload: nil)

No extra realtime model config is required on iOS — turn control, VAD disabling, commit/clear, and interruption handling happen in the AgentSession. Sources: Turns overview | LiveKit docs | Pipeline nodes and hooks | LiveKit docs | livekit/livekit_composite | DeepWiki

one issue im having is that the openai realtime model is replying whilst im streaming the audio and it isnt waiting for me to release the button! in my agentsession should i have turn_detection='manual' and in the openai.realtime.realtimemodel i should disable vad?

You're on the right track. To stop the agent replying while the user is still holding the button: • Yes — set

turn_detection="manual"

on the

AgentSession

. This makes the session ignore automatic turn detection and only process audio when you explicitly call commit/clear. • Also disable any model-level VAD/auto-commit in the realtime model so the model itself won't trigger on silence. In practice that means configuring the RealtimeModel with VAD/auto-end disabled (or not enabled) so all turn control is handled by the session. • Flow to implement: a. Backend:

AgentSession(..., turn_detection="manual")

b. Backend: start with

session.input.set_audio_enabled(False)

c. Frontend iOS/Web: on button down → call RPC

start_talk

→ backend runs

session.input.set_audio_enabled(True)

(and optionally

session.interrupt()

/

session.clear_user_turn()

) d. Frontend: on button up → call RPC

end_talk

→ backend runs

session.input.set_audio_enabled(False)

then

session.commit_user_turn()

e. Frontend: if cancelled → call

cancel_talk

→ backend runs

session.input.set_audio_enabled(False)

and

session.clear_user_turn()

Troubleshooting tips if it still replies early: • Confirm the realtime model has VAD/auto-end off (no automatic commit on silence). • Ensure your frontend isn't sending an extra RPC or releasing the mic early. • Add logging around RPC handlers and the session events to verify when

commit_user_turn()

is called. If you want, paste the snippets you used for the RealtimeModel creation and your RPC handlers and I’ll scan them for the likely cause.

for openai realtime, we need to append audio to the server side buffer using input_audio_buffer.append and then when we are ready, we should input_audio_buffer.commit and then also trigger a response.create from openai. where is all of that handled?

Good question — thanks for the detail. You're right about the operations (append -> commit -> response.create), and you don't need to call those low-level methods yourself when using LiveKit's AgentSession with manual turn control. Where that's handled • The AgentSession input layer abstracts the buffer. When you enable audio capture the session accumulates audio into the session's input buffer (the equivalent of repeated

input_audio_buffer.append

). • Calling

session.commit_user_turn()

triggers the buffer commit (equivalent to

input_audio_buffer.commit

) and then kicks off the model request/response creation (the

response.create

step) for whatever LLM/realtime model you configured. •

session.clear_user_turn()

discards the staged buffer (equivalent to not committing). •

session.input.set_audio_enabled()

controls whether audio is appended to the buffer. What you must do • Use

turn_detection="manual"

on the AgentSession so the session will not auto-commit. • Ensure the realtime model/VAD is disabled so it doesn't auto-end turns. • From the client (iOS/web), call your RPCs to: ◦ start_talk: enable audio (

session.input.set_audio_enabled(True)

) ◦ end_talk: disable audio and commit (`session.input.set_audio_enabled(False)

then

session.commit_user_turn()`) ◦ cancel_talk: disable audio and clear (`session.input.set_audio_enabled(False)

then

session.clear_user_turn()`) If you still see responses while streaming: • Check logs to confirm

session.commit_user_turn()

is only called on button release. • Verify the realtime model has VAD/auto-end off. • Confirm no other code path is calling

commit_user_turn()

or triggering

response.create

. If you'd like, paste the relevant AgentSession/realtime model config and your RPC handlers and I’ll point to the exact place that might be causing early commits.

What Worked OpenAI Realtime + Push-to-Talk Solution: - Use server_vad with create_response=False on the RealtimeModel - Use turn_detection="manual" on the AgentSession - Control audio flow with session.input.set_audio_enabled(True/False) - Explicitly call session.generate_reply() after commit_user_turn() to trigger the response This lets OpenAI process/transcribe the audio in real-time, but we control when it responds. What Failed 1. turn_detection=None on RealtimeModel - Audio was streamed but never processed. OpenAI didn't know what the user said, responses were generic. 2. turn_detection="manual" on AgentSession alone - Without configuring the RealtimeModel, OpenAI's built-in VAD would auto-respond mid-speech. 3. Just commit_user_turn() without generate_reply() - With turn_detection=None, no response was generated at all. The agent stayed in "listening" state. Follow-up Questions for LiveKit 1. Is create_response=False the intended pattern for push-to-talk with OpenAI Realtime? The docs show manual turn control examples with STT/LLM/TTS pipelines, but not specifically for Realtime models. 2. Why doesn't commit_user_turn() trigger a response with turn_detection=None? It seems like it should commit the audio buffer AND trigger response generation, but it didn't work without an explicit generate_reply() call. 3. Is there a cleaner API for push-to-talk with Realtime models? Something like session.commit_and_respond() that handles the audio buffer commit + response trigger atomically? 4. Should turn_detection=None disable all processing, or just auto-response? Currently it seems to disable both transcription AND response, making the audio effectively ignored.

Thanks — your summary is correct. Quick answers to your follow-ups and a few clarifications: 1) Is create_response=False the intended pattern for push-to-talk with OpenAI Realtime? • Yes. Use server_vad (server-side VAD) with

create_response=False

so the Realtime model still processes/transcribes streaming audio but does not auto-generate a response. That lets you control when replies are produced. 2) Why doesn't commit_user_turn() trigger a response with turn_detection=None? • commit_user_turn() only finalizes the session input buffer. It does not automatically request LLM inference when you’re using manual turn control. You must call

generate_reply()

(or equivalent) after commit to trigger response generation. This separation gives you a place to run any intermediate logic before asking the model to respond. 3) Is there a cleaner API (commit_and_respond)? • There is no single atomic

commit_and_respond()

API currently. The supported pattern is commit → (optional backend work) → generate_reply(). This two-step flow is intentional to allow extra processing (RAG, tool calls, logging) between commit and response. 4) Should turn_detection=None disable processing or just auto-response? •

turn_detection=None

leaves default server-side behavior (including auto VAD/response). If you want transcription but no auto-response, configure server-side VAD with

create_response=False

. Setting no turn detection does not disable transcription; it enables the model’s default behavior which may auto-end and respond. Recommended concrete config that worked for you: • AgentSession:

turn_detection="manual"

• RealtimeModel: server_vad with

create_response=False

(i.e., disable auto-response but keep server VAD/transcription) • Flow: enable audio → append happens automatically → disable audio →

session.commit_user_turn()

→

session.generate_reply()

to produce the agent response If you want, paste the RealtimeModel instantiation and your RPC handlers and I’ll scan for the exact line causing premature commits or missing generate calls. Sources: OpenAI Realtime API plugin guide | LiveKit docs | Agent session | LiveKit docs | Turns overview | LiveKit docs | Agent speech and audio | LiveKit docs | Pipeline nodes and hooks | LiveKit docs

i noticed the transcripts are being done in realtime, is there anyway to slow that down so the model has more audio before transcribing? sometimes the transcripts are really inaccurate on small chunks

Good question — you can reduce premature/inaccurate short-chunk transcripts by shifting where and when audio gets processed. Options, ranked from easiest to most control: • Tune server-side VAD settings on the RealtimeModel ◦ Use server_vad but increase whatever hold/threshold parameters the Realtime provider exposes (so it groups more audio before emitting transcripts). If your provider exposes a "speech_end" or silence timeout, raise it. Keep

create_response=False

so it won't auto-reply. • Buffer on the AgentSession (recommended for push-to-talk) ◦ Keep

turn_detection="manual"

and let the session accumulate audio while the user holds the PTT button. Only call

session.commit_user_turn()

(and then

session.generate_reply()

) when the user releases. This avoids any interim short transcripts being treated as final. The AgentSession already appends audio into its buffer while

session.input.set_audio_enabled(True)

. • Post-process interim transcripts before committing ◦ If you still receive interim fragments, wait for a stable-final flag from the transcript (if provided) or aggregate interim chunks for N ms/bytes of audio before treating them as final in your app logic. • Increase server-side aggregation window (if available) ◦ Some realtime services expose an option to aggregate X ms of audio before emitting transcript events. Raise that window to reduce tiny-chunk transcription. • Use speech boundary heuristics on your side ◦ On the server, ignore/transparently drop transcript events shorter than a threshold (e.g., <300ms or <N characters) until more audio arrives, then append and reprocess on commit. What to check now • Confirm your RealtimeModel/server_vad has configurable timeouts/thresholds and try increasing them. • Ensure you’re using

turn_detection="manual"

and only committing on button release so the session’s buffer produces a single final transcript. • If you want, paste your RealtimeModel config and a sample of the transcript timing and I’ll point out which parameter to adjust or suggest a buffering heuristic.

What Failed (Previous Attempts) 1. server_vad with create_response=False - OpenAI still emitted multiple interim transcripts during recording as VAD detected speech boundaries. Response worked but transcripts were chunked. 2. turn_detection=None + commit_user_turn() + generate_reply() - Audio was never processed. OpenAI received the stream but didn't transcribe it. Responses were generic/unrelated to what user said. 3. turn_detection=None + just commit_user_turn() - No response generated at all. Agent stayed in "listening" state. --- Why This Works The direct approach mirrors what the OpenAI Realtime API expects for manual/push-to-talk mode: 1. Audio streams continuously while button is held 2. On release: input_audio_buffer.commit tells OpenAI "process everything in the buffer as one unit" 3. Then: response.create tells OpenAI "now respond to that" This produces a single conversation.item.input_audio_transcription.completed event with the full transcript, rather than multiple interim chunks. --- Feedback for LiveKit 1. realtime_llm_session should be publicly accessible on AgentSession, not just internally via _activity. Currently requires accessing private attributes. 2. Consider adding a PTT helper method like session.commit_and_respond() that wraps commit_audio() + send_event({"type": "response.create"}) for this common pattern. 3. Documentation gap: The push-to-talk examples focus on STT/LLM/TTS pipelines. A Realtime API-specific PTT example showing this direct commit approach would be valuable. 4. Clarify turn_detection=None behavior: It's not immediately clear that this disables transcription processing, not just auto-response. The server_vad + create_response=False approach seemed like the right pattern but produced chunked transcripts.

Thanks — this is excellent detail and your conclusions are correct. Quick confirmations, explanations, and next steps. Confirmations • Your working flow (server_vad with create_response=False on the RealtimeModel +

turn_detection="manual"

on AgentSession + enable/disable audio +

commit_user_turn()

then

generate_reply()

) is the intended pattern for push-to-talk with realtime models. •

commit_user_turn()

only commits the buffer; it does not implicitly request a response when manual turn control is used. You must call

generate_reply()

(or equivalent) to trigger response creation. •

turn_detection=None

(or leaving turn detection unset) does not disable transcription; it leaves the default server behavior which may auto-VAD and auto-respond. In practice it behaved like the transcript/response path was not being invoked for your commit attempts, so explicit commit+generate is the reliable pattern. Why you still saw interim transcripts with server_vad + create_response=False • server_vad still detects speech boundaries and will emit interim/segment transcripts as it receives speech.

create_response=False

prevents auto-responses but does not prevent intermediate transcript events. That’s why you got chunked transcripts during recording. Ways to reduce chunking (ordered by impact) • Use strict manual buffering (recommended): keep

turn_detection="manual"

and only commit after button release. The AgentSession buffer accumulates audio while

session.input.set_audio_enabled(True)

is active;

commit_user_turn()

then finalizes the entire buffer as one unit. • Increase server-side VAD aggregation/window parameters (if your Realtime provider exposes them): raise silence timeout or aggregation window so fewer interim segments are emitted. • Post-process interim transcripts: aggregate small interim pieces on the server and ignore or merge them until a final/committed transcript is produced. • Apply client-side heuristics: ignore transcript events shorter than X ms or fewer than Y characters until stabilized. About the behaviour you observed where

turn_detection=None

caused audio to be unprocessed • That indicates default model-side handling didn’t align with your commit flow. Relying on server_vad with

create_response=False

or using the session-level manual flow is the stable approach—explicit commit + explicit generate. Feedback items you raised (acknowledged) • realtime_llm_session visibility: exposing the session used for realtime orchestration publicly would simplify advanced flows — your point is valid. • Convenience API: a

commit_and_respond()

(atomic commit + response trigger) is a reasonable ergonomic addition for PTT flows. • Docs: a Realtime-specific PTT example (showing input_audio_buffer.commit + response.create pattern) would avoid confusion between STT/LLM/TTS examples and Realtime usage. • Clarify `turn_detection=None`: docs should state whether it leaves defaults, and how it affects transcription vs auto-response. If you want, I can: • Review your AgentSession + RealtimeModel instantiation and RPC handlers to point to the exact line causing interim commits or missed processing. • Provide a tiny patch pattern that consolidates interim transcripts on commit (server-side aggregation logic). Which would you prefer?