I'm using the OpenAI Realtime model for both STT a...
# ask-aim
mysterious-agent-76276
08/17/2025, 8:24 AMI'm using the OpenAI Realtime model for both STT and LLM capabilities, while my TTS is handled by a separate provider. For some reason, at random times, the conversation gets stuck after I say something, then I have to say "hello?" or continue talking for it to detect speech again. I want it to be as smooth as possible. I have a suspicion it might be due to the turn detection, but I could be wrong. Here's my model config:
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openai.realtime.RealtimeModel(
model="gpt-4o-realtime-preview",
modalities=["text"],
temperature=0.6,
turn_detection=TurnDetection(
type="server_vad",
threshold=0.6,
prefix_padding_ms=100,
silence_duration_ms=120,
create_response=True,
interrupt_response=False,
),
)t
tall-airline-16756
08/17/2025, 8:24 AMThanks for reaching out, Anas. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
tall-airline-16756
08/17/2025, 8:25 AMIt sounds like the speech detection interruptions you're facing might be tied to how the
server_vadthresholdsilence_duration_msprefix_padding_ms Copy code
TurnDetection(
type="server_vad",
threshold=0.4,
prefix_padding_ms=300,
silence_duration_ms=700,
create_response=True,
interrupt_response=True,
)m
mysterious-agent-76276
08/17/2025, 8:25 AMis there any better option for ultra-low latency?
t
tall-airline-16756
08/17/2025, 8:25 AMTo help you get the absolute lowest latency in your setup, here are some friendly tips you might find useful:
• Use WebRTC: WebRTC is great for low-latency audio chats because it handles packet loss better and adjusts bitrate on the fly, unlike WebSocket.
• Optimize Turn Detection: Tweaking settings like
thresholdprefix_padding_mssilence_duration_msserver_vadm
mysterious-agent-76276
08/17/2025, 8:34 AMis semantic_vad lower latency?
t
tall-airline-16756
08/17/2025, 8:35 AMHey there! I don’t have exact info on how the latency of
semantic_vadserver_vadm
mysterious-agent-76276
08/17/2025, 8:44 AMis it better to set the turn detection in the
AgentSessionRealtimeModelt
tall-airline-16756
08/17/2025, 8:45 AMTo get the best performance, it’s a good idea to set up turn detection right in the
RealtimeModelAgentSessionRealtimeModelm
mysterious-agent-76276
08/17/2025, 9:19 AMI'm hitting this error:
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2025-08-17 17:17:18 | ERROR | livekit.plugins.openai | realtime_model.py:_recv_task:790 | failed to handle event
Traceback (most recent call last):
File "/venv/lib/python3.13/site-packages/livekit/plugins/openai/realtime/realtime_model.py", line 770, in _recv_task
self._handle_response_audio_delta(
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
ResponseAudioDeltaEvent.construct(**event)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/venv/lib/python3.13/site-packages/livekit/plugins/openai/realtime/realtime_model.py", line 1362, in _handle_response_audio_delta
item_generation.audio_ch.send_nowait(
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
rtc.AudioFrame(
^^^^^^^^^^^^^^^
...<4 lines>...
)
^
)
^
File "/venv/lib/python3.13/site-packages/livekit/agents/utils/aio/channel.py", line 95, in send_nowait
raise ChanClosed
livekit.agents.utils.aio.channel.ChanClosedt
tall-airline-16756
08/17/2025, 9:20 AMHey there! The
ChanClosedaudio_chResponseAudioDeltaEvent_handle_response_audio_delta Copy code
def _handle_response_audio_delta(self, event: ResponseAudioDeltaEvent) -> None:
assert self._current_generation is not None, "current_generation is None"
item_generation = self._current_generation.messages[event.item_id]
if not item_generation.modalities.done():
item_generation.modalities.set_result(["audio", "text"])
data = base64.b64decode(event.delta)
if not item_generation.audio_ch.closed:
item_generation.audio_ch.send_nowait(
rtc.AudioFrame(
data=data,
sample_rate=SAMPLE_RATE,
num_channels=NUM_CHANNELS,
samples_per_channel=len(data) // 2,
)
)m
mysterious-agent-76276
08/19/2025, 6:44 AMfor some reason, the LLM stops generating a response after the STT after a few interactions. I can see the transcription of what I said, but it's not triggering tts_node
t
tall-airline-16756
08/19/2025, 6:45 AMIt sounds like the LLM stopping after STT transcription might be because the turn detection isn’t quite marking the end of the user’s turn properly. No worries though—here are a few things you can try to get things running smoothly:
• Make Sure Turn Detection Is Set Up Right: Try using a reliable turn detection mode like
server_vadturn_detection="stt"AgentSessioncommit_user_turn()RealtimeModelmodalities=["text"]m
mysterious-agent-76276
08/19/2025, 6:45 AMhere
mysterious-agent-76276
08/19/2025, 6:45 AM Copy code
self._llm = openai.realtime.RealtimeModel(
model=self.config.llm.openai_model,
modalities=["text"],
temperature=self.config.llm.temperature,
turn_detection=TurnDetection(
type="server_vad",
threshold=0.5,
prefix_padding_ms=200,
silence_duration_ms=500,
create_response=True,
interrupt_response=False,
),
)t
tall-airline-16756
08/19/2025, 6:46 AMHey there! Your setup with
server_vadsilence_duration_ms=500threshold=0.5create_response=Truem
mysterious-agent-76276
08/19/2025, 9:58 AMit still stops talking altogether after a few interactions
t
tall-airline-16756
08/19/2025, 9:59 AMHey there! If your LLM stops generating responses after a few interactions, don’t worry—here are some common reasons and easy fixes to check out:
• Generation Finished Reasons: Sometimes responses stop because of things like token limits, content filters, or interruptions. Take a peek at your settings and tweak them if needed.
• StopResponse Triggers: Double-check your
on_user_turn_completedStopResponsem
mysterious-agent-76276
08/19/2025, 10:35 AMthe LLM is suddenly returning a string similar to this "{"edits": [{"path": "...", "start_line": ..., "end_line": ...}]}"
t
tall-airline-16756
08/19/2025, 10:36 AMHey there! When the LLM sends back a JSON-like string with edits instead of a regular response, it usually means the API switched to text mode instead of audio mode. This can happen if conversation history is loaded into the model or because of how responses are handled.
Here are some steps that might help you fix this:
• Use Recovery Logic: Try adding a recovery method that handles text responses and then requests a new audio response. For example:
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recoverFromTextResponse(itemId: string) {
if (itemId) {
this.conversation.item.delete(itemId);
}
this.conversation.item.create(this.#createEmptyUserAudioMessage(1));
this.response.create();
}ResponseTextDeltaEventm
mysterious-agent-76276
08/19/2025, 10:37 AMI'm already using a separate TTS plugin. The LLM is working fine for a few interactions, then suddenly it starts returning code
t
tall-airline-16756
08/19/2025, 10:38 AMHey there! That hiccup where the LLM starts giving code-like responses after a few chats usually happens because the API switches from audio responses to text-only ones. This can pop up when the conversation history loads or if there's a lot of back-and-forth.
Here’s a friendly checklist to help you fix it:
• Separate TTS Plugin: Since you’re already using a separate TTS plugin, double-check that the LLM is set for text-only responses (
modalities=["text"] Copy code
recoverFromTextResponse(itemId: string) {
if (itemId) {
this.conversation.item.delete(itemId);
}
this.conversation.item.create(this.#createEmptyUserAudioMessage(1));
this.response.create();
}m
mysterious-agent-76276
08/19/2025, 11:08 AMif it suddenly switches to text mode, how can I switch it back? would manually calling generate_reply work?
t
tall-airline-16756
08/19/2025, 11:09 AMHey there! Manually calling
generate_replyresponse.create()m
mysterious-agent-76276
08/19/2025, 11:39 AMI can't find the function
_recover_from_text_responset
tall-airline-16756
08/19/2025, 11:40 AMHey there! Just a heads-up: the function
_recover_from_text_responserecoverFromTextResponsem
mysterious-agent-76276
08/19/2025, 11:41 AMI'm using the python sdk
t
tall-airline-16756
08/19/2025, 11:42 AMHey there! Just wanted to share a quick tip about the Python SDK — it automatically handles recovery from text responses by falling back to a TTS model whenever the Realtime API sends text instead of audio. To make sure this works smoothly for you, just set up your agent with both the Realtime model and a TTS model like this:
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agent = Agent(
instructions="Your instructions here",
llm=openai.realtime.RealtimeModel(voice="alloy", model="gpt-4o-mini-realtime-preview"),
tts=openai.TTS(voice="alloy"),
chat_ctx=chat_ctx,
) Copy code
session = AgentSession(
llm=openai.realtime.RealtimeModel.with_azure(
# ... endpoint and auth params ...,
modalities=["text"]
),
tts=cartesia.TTS() # Or any other TTS plugin you prefer
)m
mysterious-agent-76276
08/19/2025, 3:39 PMis there a way to stop it from triggering tts_node if the LLM fails? I worry that even though it falls back to the TTS, it's still triggering tts_node, which I'm overriding
t
tall-airline-16756
08/19/2025, 3:41 PMHey there! To help you avoid the TTS fallback from triggering
tts_node Copy code
agent = Agent(
instructions="You are a helpful assistant.",
stt=deepgram.STT(),
llm=openai.LLM(),
vad=silero.VAD.load()
)tts_node Copy code
class NoFallbackAgent(Agent):
async def tts_node(self, text, model_settings):
async def empty_audio():
return
yield
return empty_audio() Copy code
session.output.set_audio_enabled(False) Copy code
@session.on("error")
def on_error(ev):
if ev.error.recoverable:
ev.error.recoverable = False