how to make agent wait for user to speal all 10 di...
# ask-aic
clever-apartment-50437
09/17/2025, 1:41 PMhow to make agent wait for user to speal all 10 digit phone number before continue to talk considering they might um,uh for about 3seconds
t
tall-airline-16756
09/17/2025, 1:41 PMThanks for reaching out, Hai. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
tall-airline-16756
09/17/2025, 1:42 PMI understand how important it is for the agent to patiently wait while the user speaks all 10 digits of their phone number, including those natural pauses like "um" or "uh." To help with this, you can adjust the
min_endpointing_delaysilero.VAD.load()min_endpointing_delay Copy code
agent = VoicePipelineAgent(
vad=silero.VAD.load(),
stt=deepgram.STT(),
llm=openai.LLM(),
tts=cartesia.TTS(),
min_endpointing_delay=3.0 # Wait up to 3 seconds of silence before ending turn
)c
clever-apartment-50437
09/17/2025, 1:47 PMwhat about when user say 571 umm uhh 505 uhmmm 1131?
t
tall-airline-16756
09/17/2025, 1:47 PMI completely understand how tricky it can be when users include pauses and fillers like "umm" or "uhh" while saying a phone number (for example, "571 umm uhh 505 uhmmm 1131"). To help you navigate this smoothly, here are some friendly strategies you can try:
1. Enable Context-Aware Turn Detection: Consider using LiveKit's turn detection model, such as
MultilingualModelon_user_turn_completed() Copy code
class PhoneNumberAgent(Agent):
async def on_user_turn_completed(self):
raw_text = self.chat_ctx.messages[-1].text
cleaned = self._extract_phone_number(raw_text)
if cleaned:
await self.session.generate_reply(f"Got it, your number is {cleaned}.")c
clever-apartment-50437
09/17/2025, 2:00 PMCould not find model livekit/turn-detector with revision v0.3.0-intl. Make sure you have downloaded the model before running the agent. Use
python3 your_agent.py download-filest
tall-airline-16756
09/17/2025, 2:01 PMIt looks like the error is telling us that the model
livekit/turn-detectorv0.3.0-intlyour_agent.pynode ./your_agent.ts download-files~/.cache/huggingface/hub~/.cache/huggingface/hub/models--livekit--turn-detectorc
clever-apartment-50437
09/17/2025, 2:35 PMcan i use this instead
t
tall-airline-16756
09/17/2025, 2:35 PMI completely understand how this might be a bit confusing, so let me help clarify things for you! The
StopResponsetall-airline-16756
09/17/2025, 2:41 PMThank you for reaching out! While the exact code example from the video at isn’t directly available in the documentation, I’m happy to share some helpful examples on how you can implement LiveKit's turn detection:
1. Using the MultilingualModel with a Realtime LLM (Python):
Copy code
session = AgentSession(
turn_detection=MultilingualModel(),
vad=ctx.proc.userdata["vad"],
stt=deepgram.STT(),
llm=openai.realtime.RealtimeModel(
voice="alloy",
turn_detection=None,
input_audio_transcription=None,
),
) Copy code
const session = new voice.AgentSession({
turnDetection: new livekit.turnDetector.EnglishModel(),
}); Copy code
const eouModel = new turnDetector.MultilingualModel();
const result = await eouModel.predictEndOfTurn(chatCtx);t
tall-airline-16756
09/17/2025, 2:41 PMThank you for reaching out! I wanted to let you know that the specific code example shown in the video at isn’t directly available in the documentation or knowledge base. But no worries—I’m happy to share some helpful examples on how you can implement LiveKit’s turn detection model, just like in the video:
1. Using the MultilingualModel (Python):
Copy code
session = AgentSession(
turn_detection=MultilingualModel(),
vad=ctx.proc.userdata["vad"],
stt=deepgram.STT(),
llm=openai.realtime.RealtimeModel(
voice="alloy",
turn_detection=None,
input_audio_transcription=None,
),
) Copy code
const session = new voice.AgentSession({
turnDetection: new livekit.turnDetector.EnglishModel(),
});tall-airline-16756
09/17/2025, 2:41 PMThank you for reaching out! The specific code example shown in the video at isn’t directly available in the documentation or knowledge base. But don’t worry—I’m happy to share some helpful examples on how to implement LiveKit's turn detection model, which is likely what’s demonstrated in the video:
1. Using the MultilingualModel (Python):
Copy code
session = AgentSession(
turn_detection=MultilingualModel(),
vad=ctx.proc.userdata["vad"],
stt=deepgram.STT(),
llm=openai.realtime.RealtimeModel(
voice="alloy",
turn_detection=None,
input_audio_transcription=None,
),
) Copy code
const session = new voice.AgentSession({
turnDetection: new livekit.turnDetector.EnglishModel(),
});c
clever-apartment-50437
09/17/2025, 2:53 PMis this correct? session = AgentSession(
_turn_detection_=MultilingualModel(),
llm = openai.LLM(model="gpt-4.1-mini"),
stt = deepgram.STT(
model="nova-3",
language="multi",
),
tts = inworld.TTS(
model="inworld-tts-1-max",
temperature=1.0,
pitch=0.0
),
# Stricter turn-taking: rely on VAD only (disable turn detector due to errors)
vad=ctx.proc.userdata.get("vad"),
_allow_interruptions_=False,
_min_endpointing_delay_=3.5,
_max_endpointing_delay_=6.0,
)
t
tall-airline-16756
09/17/2025, 2:53 PMThank you for sharing your configuration with me! I see you’re using
MultilingualModelc
clever-apartment-50437
09/17/2025, 2:54 PMit just cant pass this test case
clever-apartment-50437
09/17/2025, 2:54 PM4) “Thinking” after order prompt (no reprompt)
• Agent: “What would you like to order?”
• User: “Let me think…” then silence 5–7s.
• Expect: Agent stays silent during this window (no “what would you like” reprompt). If still silent after ~8s, agent may gently suggest popular items.
t
tall-airline-16756
09/17/2025, 2:55 PMTo gently handle the test case where the user says "Let me think..." followed by 5–7 seconds of silence, and to ensure no reprompt during this quiet moment with a kind suggestion after about 8 seconds, here’s a friendly way to set up your LiveKit AgentSession:
1. Set `user_away_timeout`: This helps trigger a soft prompt after 8 seconds of silence:
Copy code
session = AgentSession(
user_away_timeout=8.0, # Changes user_state to 'away' after 8 seconds
min_endpointing_delay=0.4, # Allows short pauses within speech
max_endpointing_delay=6.0, # Max silence before forced endpoint
stt=deepgram.STT(),
tts=openai.TTS(),
vad=silero.VAD.load(),
llm=openai.LLM()
)user_state_changed Copy code
@session.on("user_state_changed")
def on_user_state_changed(state):
if state == "away":
session.say("Still thinking? Let me know when you're ready.", allow_interruptions=True) Copy code
async def on_user_turn_completed(chat_ctx, message):
if "let me think" in message.text.lower():
await session.say("Take your time!", add_to_chat_ctx=False)c
clever-apartment-50437
09/17/2025, 2:56 PMi only want to use turn dector plugin
t
tall-airline-16756
09/17/2025, 2:57 PMHi there! I wanted to share some important info about the LiveKit turn detector plugin. It can’t work on its own—it actually needs a speech-to-text (STT) plugin to convert speech into text, which it then uses to understand the flow of conversation. For example, it picks up on cues like when someone says, "Let me think..." and pauses.
Here’s why the STT plugin is essential:
• The turn detector looks at the transcribed text to figure out if the speaker plans to continue or has finished their turn.
• It relies on STT output to catch phrases like "Let me think..." and decide how to handle silences appropriately.
While the Silero VAD plugin is a helpful addition for handling interruptions smoothly, it’s optional. But the STT plugin is definitely a must-have for the turn detector to do its job.
If you’re ready to set up the turn detector, here’s a simple way to configure it:
Copy code
from livekit.plugins.turn_detector.english import EnglishModel
from livekit.plugins import deepgram
session = AgentSession(
turn_detection=EnglishModel(),
stt=deepgram.STT(model="nova-3", language="en"), # Required
# vad=silero.VAD.load(), # Optional but recommended
# ... other components
)