I want to use manual turn detection: session = Age...
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b
I want to use manual turn detection: session = AgentSession( vad=None, turn_detection="manual", ) How do I implement in the backend and in the frontend this? My goal is to create a push to talk interface on the frontend: while I push a button the Agent listens to me, when I release it it answers. The audio should be processed all together by the STT when I release the button, not in small parts independently, as I think this could degrade the overall accuracy of the STT model as it would have less context
t
Thanks for reaching out, aile. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
To implement manual turn detection for a push-to-talk interface, follow these steps: 1. Session Configuration:`session = AgentSession( turn_detection="manual", stt=your_stt_provider.STT(), # ... other components ) session.input.set_audio_enabled(False)` ◦ Set up the
AgentSession
with manual turn detection and disable audio input initially: 1. Push-to-Talk Implementation:`# When user starts speaking (button press) @ctx.room.local_participant.register_rpc_method("start_turn") async def start_turn(data: rtc.RpcInvocationData): session.interrupt() # Stop any current agent speech session.clear_user_turn() # Clear any previous input session.input.set_audio_enabled(True) # Start listening # When user finishes speaking (button release) @ctx.room.local_participant.register_rpc_method("end_turn") async def end_turn(data: rtc.RpcInvocationData): session.input.set_audio_enabled(False) # Stop listening session.commit_user_turn( transcript_timeout=10.0, # Timeout for final transcript ) # When user cancels their turn @ctx.room.local_participant.register_rpc_method("cancel_turn") async def cancel_turn(data: rtc.RpcInvocationData): session.input.set_audio_enabled(False) # Stop listening session.clear_user_turn() # Discard the input` ◦ Use RPC methods to control the audio input lifecycle: 1. Audio Processing as a Whole: ◦ The
commit_user_turn()
method ensures that the entire audio segment is processed by the STT after the button is released. It waits for the final transcript and processes the input as a complete segment. 1. Complete Example:`async def entrypoint(ctx: JobContext): session = AgentSession(turn_detection="manual") room_io = RoomIO(session, room=ctx.room) await room_io.start() agent = MyAgent() # Your agent implementation await session.start(agent=agent) session.input.set_audio_enabled(False) # Disable input audio at the start @ctx.room.local_participant.register_rpc_method("start_turn") async def start_turn(data: rtc.RpcInvocationData): session.interrupt() session.clear_user_turn() room_io.set_participant(data.caller_identity) # Listen to the caller session.input.set_audio_enabled(True) @ctx.room.local_participant.register_rpc_method("end_turn") async def end_turn(data: rtc.RpcInvocationData): session.input.set_audio_enabled(False) session.commit_user_turn(transcript_timeout=10.0)` ◦ Here’s a full implementation: This setup ensures that the STT processes the complete audio segment captured between button press and release, providing accurate transcription of the entire user utterance before generating a response. Sources: Turn detection and interruptions | LiveKit Docs | livekit-plugins/livekit-plugins-turn-detector/README.md
b
How do I implement the frontend starting from the basic Next.js frontend template provided by livekit?
t
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!