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I am using livekit.plugins.turn_detector.english e...
# ask-ai
h
I am using livekit.plugins.turn_detector.english english model for turn detection. when does the status change from listening to thinking? once user stop speaking or once STT is done transcripting the speech?? what is the flow?
t
Thanks for reaching out, Abhishek. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
Let me walk you through how the status in the 
livekit.plugins.turn_detector.english
model changes from listening to *thinking*—this happens when the system senses that you’ve finished your turn in the conversation. Here’s how it works: • User is Speaking: While you’re talking, the agent stays in the listening state, gathering your audio and using speech-to-text (STT) to transcribe what you say in real-time. • Speech Pauses: When you pause or stop speaking, voice activity detection (VAD) notices the silence and starts a timer. • Contextual Analysis: The turn detector model then looks at the transcription and the recent conversation (it checks the last four turns) to decide if you’ve likely finished speaking. • Decision to Transition: If the model thinks your turn is complete, the agent switches to thinking mode to process your input further. There are some important settings that help this process run smoothly: • min_endpointing_delay: This is the minimum silence time (usually 500ms) before the system considers your turn done. • max_endpointing_delay: This is the maximum wait time (default 6.0s) if the model thinks you might still be speaking. All of this is designed to make sure the agent doesn’t interrupt you during natural pauses and only moves on when you’ve probably finished your thought. If you have any questions or want to dive deeper, I’m here to help! Sources: Improving voice AI's turn detection with transformers | Events and error handling | LiveKit Docs | LiveKit turn detector plugin | LiveKit Docs | AI voice agents | LiveKit Docs
a
I'm using STT as deepgram, using update_options, can I change the VoicePipelineAgent's STT from deepgram to Azure.stt??
t
Thanks for reaching out! Just to make sure I understand correctly, are you asking about switching the STT provider on the fly during an active session (like moving from Deepgram to Azure.stt), or are you looking to set Azure.stt as your default STT provider for future sessions? Once I know this, I’ll be happy to guide you through the best way to proceed.
a
Yes, you get it right, I want to change the STT provider on the fly during an active session for my VoicePipelineAgent
t
Thanks for reaching out! I understand you'd like to change the STT provider (like switching from Deepgram to Azure STT) within an active 
VoicePipelineAgent
instance. While you can’t directly change it on the fly, don’t worry—you can smoothly switch by replacing your current agent with a new one configured for the STT provider you want. Here are two friendly ways to do that: 1. Using `llm.handoff()`: This approach hands over control to a new agent instance set up with your chosen STT provider. For example:
Copy code
@function_tool
async def switch_stt_provider(self, stt_choice: str):
    stt_provider = {
        "deepgram": deepgram.STT(),
        "azure": azure.STT(speech_key="your-key", speech_region="your-region")
    }.get(stt_choice)
    
    if not stt_provider:
        return "STT provider not supported"
        
    return llm.handoff({
        agent: new VoicePipelineAgent({
            stt: stt_provider,
            llm: self.llm,
            tts: self.tts,
            vad: self.vad
        }),
        returns: "Switched to " + stt_choice
    })
1. Using `session.update_agent()`: This method swaps out the current agent for a new one configured with your desired STT provider:
Copy code
@function_tool
async def change_stt(self):
    new_agent = VoicePipelineAgent(
        vad=self.vad,
        stt=azure.STT(),
        llm=self.llm,
        tts=self.tts,
        chat_ctx=self.chat_ctx
    )
    self.session.update_agent(new_agent)
    await new_agent.say("STT provider changed to Azure")
Both options keep your session going smoothly! Just remember to set up the new STT provider (like Azure STT) with the right credentials when you initialize it. If you’d like, I’m here to help you with any part of the implementation—just let me know! Sources: examples/src/comprehensive_test.ts | multi-agent/long_or_short_agent.py | Events and error handling | LiveKit Docs | livekit-plugins/livekit-plugins-azure/livekit/plugins/azure/stt.py
a
This is not agent v1.0 but the earlier one.. is this applicable to this as well?
t
I completely understand how important it is to have flexibility with your STT provider. In versions of 
VoicePipelineAgent
before v1.0, the STT provider is set when the agent starts and can’t be changed during an active session. The great news is that starting with v1.0, we introduced the 
AgentSession
framework and the 
llm.handoff()
function, which allow dynamic switching of providers, including during agent handoffs. If upgrading to v1.0 right away isn’t an option, one possible workaround is to run multiple agents with different STT setups and route sessions between them manually based on your own logic. I want to be upfront that this method requires quite a bit of custom session management and isn’t officially supported, but it could be a helpful temporary solution. For the smoothest experience with dynamic STT switching, I’d definitely recommend upgrading to v1.0 or later. Please feel free to reach out if you’d like some guidance on how to implement this in v1.0 or if you want to explore how to set up a multi-agent routing solution with your current setup—I’m here to help! Sources: VoicePipelineAgent | LiveKit Docs | Agents 0.x migration guide | LiveKit Docs | Working with plugins | LiveKit Docs | Agents v0.x migration guide - Node.js | LiveKit Docs | LiveKit integration guides | LiveKit Docs
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