We currently have a voice agent implemented using ...
# ask-ai
j
We currently have a voice agent implemented using automatic turn detection (VAD) that works well, but we'd like to add push-to-talk (PTT) functionality as an option for users who prefer more explicit control over when they're speaking. ## Current Implementation Our agent uses:
Copy code
python
session = AgentSession(
    _stt_=deepgram.STT(
        _model_="nova",
        _interim_results_=False,
        _endpointing_ms_=4000,
        _punctuate_=True,
        _smart_format_=True
    ),
    _tts_=deepgram.TTS(_model_="aura"),
    _vad_=silero.VAD.load(),
    _turn_detection_=MultilingualModel(),
    _allow_interruptions_=False,
    _min_interruption_duration_=0.5,
    _min_endpointing_delay_=4.0,
    _max_endpointing_delay_=120.0
)
## Questions 1. Hybrid Mode Support: Is it possible to support both VAD and PTT modes in the same agent deployment? For example, could we: - Check room metadata or participant metadata on connection - Dynamically set
turn_detection="manual"
vs
MultilingualModel()
based on user preference - Or do we need separate agent deployments for each mode? 2. Graceful Degradation: If we set
turn_detection="manual"
but the client doesn't implement the RPC methods (
start_turn
,
end_turn
), what happens? Does it fall back to any default behavior or will the agent simply not receive any audio? 3. Audio Input Control Scope: When using
room.set_audio_input_enabled(False)
in PTT mode: - Does this only affect the agent's ability to receive audio from that specific participant? - Or does it affect the entire room's audio configuration? - How does this interact with multiple participants in the same room? 4. Transcript Handling in PTT: - In the PTT example,
commit_user_turn(transcript_timeout=3)
is used. What happens if the STT service hasn't returned a final transcript within this timeout? - Is the partial transcript used, or does it wait indefinitely? - How should we handle cases where users release the button mid-word? 5. State Management: - If a user is mid-sentence and accidentally releases the PTT button, then presses it again quickly, how can we ensure continuity in the conversation context? - Should we implement a "grace period" where releasing the button briefly doesn't end the turn? 6. Implementation Architecture: - Can we change turn detection mode after
session.start()
has been called? - Or must this be decided at session initialization time? 7. Client-Side Requirements: - Are there any specific client SDK versions required for PTT support? - Any example implementations for React Native/Expo clients? Any guidance on best practices for implementing PTT alongside our existing VAD setup would be greatly appreciated! Thank you,
t
Thanks for reaching out, Albert. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
Here are the answers to your questions regarding implementing Push-to-Talk (PTT) alongside your existing Voice Activity Detection (VAD) setup: 1. Hybrid Mode Support: LiveKit supports both VAD and PTT modes in the same deployment. You can dynamically set the
turn_detection
parameter based on user preferences. For example, use
turn_detection="manual"
for PTT and
turn_detection="MultilingualModel()"
for VAD. Switching modes dynamically requires reinitializing the session. 2. Graceful Degradation: If
turn_detection="manual"
is set but the client does not implement the required RPC methods (
start_turn
and
end_turn
), the agent will not receive audio or process user turns. Implementing these methods is essential for PTT functionality. 3. Audio Input Control Scope: Using
room.set_audio_input_enabled(False)
affects only the specific participant's audio input in the session, not the entire room. This ensures that other participants remain unaffected. 4. Transcript Handling in PTT: If the STT service does not return a final transcript within the
transcript_timeout
, the interim transcript (if available) will be used to commit the user turn. This ensures the process continues without indefinite waiting. 5. State Management: To ensure continuity when a user releases the PTT button mid-sentence and presses it again quickly, configure appropriate
min_endpointing_delay
and
max_endpointing_delay
. This allows brief pauses without ending the turn prematurely. 6. Implementation Architecture: Turn detection mode must be decided at session initialization and cannot be changed after
session.start()
has been called. To switch modes, a new session must be created. 7. Client-Side Requirements: For React Native/Expo clients, use
@livekit/react-native
version 2.6.2 or higher and
@livekit/react-native-webrtc
version 125.0.8 or higher. Example implementations for React Native/Expo are available to guide your setup. Let me know if you need further clarification or assistance with any specific aspect of the implementation! Sources: examples/voice_agents/push_to_talk.py | examples/voice_agents/realtime_joke_teller.py | Speech & Audio Processing | livekit/livekit_composite | DeepWiki | livekit-agents/livekit/agents/voice/agent_activity.py | VoicePipelineAgent | LiveKit Docs