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My agent is repeating lines while in a conversatio...
# ask-ai
c
My agent is repeating lines while in a conversation, also after interruption or false interruptions, the agent repeating full lines. How to stop this?
t
Thanks for reaching out, Subham. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
I completely understand how frustrating it can be when your agent repeats lines during a conversation, especially after interruptions or false interruptions. Let’s work together to smooth that out! Here are a few settings you can adjust: • Enable resume_false_interruption: This setting lets the agent pause and then pick up right where it left off if no real speech follows an interruption. Here’s an example configuration:
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session = AgentSession(
    vad=silero.VAD.load(),
    llm=openai.LLM(model="gpt-4o-mini"),
    stt=deepgram.STT(),
    tts=cartesia.TTS(),
    false_interruption_timeout=1.0,  # Wait 1 second after interruption
    resume_false_interruption=True  # Resume speech automatically if no input
)
• Tune interruption thresholds: You can adjust settings like 
min_interruption_duration
and 
min_interruption_words
to help the agent avoid reacting to brief noises or short utterances that aren’t true interruptions. • Disable interruptions: If you want the agent to finish its speech without restarting, setting 
allow_interruptions=False
will make it uninterruptible. Trying these tweaks should really help reduce those repetitive moments. If you’d like, I’m here to guide you through the implementation or answer any questions you have! Sources: How to Handle Speech Interruptions More Naturally | livekit-agents/livekit/agents/voice/agent_activity.py | Turn detection and interruptions | LiveKit Docs | VoicePipelineAgent | LiveKit Docs | VoicePipelineAgent | LiveKit Docs
c
But my problem is, the bot resumes from the middle of a sentence. How can I make it continue the conversation, but maintain context and resume lines midway. If it repeats the sentence after good interruptions it's fine.
t
I'm glad you're looking to resume from the middle of a sentence while keeping the context intact and allowing sentence repetition after valid interruptions. Here's how you can set that up: • Enable resume_false_interruption: This feature helps the agent pick up right where it left off after a false interruption. Here's an example configuration for you:
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session = AgentSession(
    vad=silero.VAD.load(),
    llm=openai.LLM(model="gpt-4o-mini"),
    stt=deepgram.STT(),
    tts=cartesia.TTS(),
    false_interruption_timeout=1.0,  # Wait 1 second after interruption
    resume_false_interruption=True  # Resume speech automatically if no input
)
• Repeat sentences after valid interruptions: You can use the 
SpeechHandle
to detect if the speech was interrupted and resend the same sentence if needed. Here's a simple example:
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handle = session.say("This is an important sentence.")
if handle.interrupted:
    session.say("This is an important sentence.")
• Preserve context: The agent will automatically keep the conversation context using 
chat_ctx
, so everything flows smoothly even after interruptions. I hope these tips help you get the behavior you're aiming for. If you have any questions or want to walk through the implementation together, just let me know—I'm here to help! Sources: livekit-agents/livekit/agents/voice/agent_activity.py | Agent speech and audio | LiveKit Docs | Agent speech and audio | LiveKit Docs | Workflows | LiveKit Docs | How to Handle Speech Interruptions More Naturally
c
explain speech handle
t
The SpeechHandle is a handy tool in LiveKit that helps you manage and control the lifecycle of agent-generated speech during conversations. It’s created whenever you use methods like 
session.say()
or 
session.generate_reply()
. Let me walk you through how it works: • Track Speech Playback: You can easily monitor whether the speech has finished playing by checking the 
done
property or simply wait for it to complete with 
wait_for_playout()
. • Handle Interruptions: If the speech gets interrupted, the 
interrupted
property will let you know. Plus, you can stop speech manually anytime using 
interrupt()
. • Control Priority: SpeechHandle lets you set priorities—high, normal, or low—so you can decide the order in which messages are played. Pretty neat, right? • Post-Speech Actions: You can also add callbacks with 
add_done_callback()
to trigger actions right after the speech finishes. Here’s a simple example to wait for speech to complete:
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handle = session.say("Processing your request...")
await handle.wait_for_playout()
And if you want to repeat speech after an interruption, you could do something like this:
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handle = session.say("This is an important sentence.")
if handle.interrupted:
    session.say("This is an important sentence.")
If you’d like me to explain anything further or share more examples, just let me know—I’m here to help! Sources: Agent speech and audio | LiveKit Docs | livekit-agents/livekit/agents/voice/agent_activity.py | agents/src/voice/events.ts
c
Sometimes my bot is repeating sentences without even interruptions, how to troubleshoot this?
t
It sounds like your bot is repeating sentences without any interruptions, and I’m here to help you work through this. Let’s try a few troubleshooting steps together to figure out what might be going on: • Check the agent logic: Take a look at event handlers like 
on_user_input_transcribed
or 
on_user_turn_completed
to make sure they aren’t accidentally causing the repetition. • Verify session settings: Double-check that 
allow_interruptions
is set up correctly both at the session level and within individual 
say()
calls. For example:
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session = AgentSession(allow_interruptions=True)
• Inspect turn detection thresholds: You might want to tweak 
min_interruption_duration
and 
min_interruption_words
to prevent any false triggers. • Check for preemptive generation: If you have 
preemptive_generation=True
, make sure responses aren’t overlapping or getting queued unnecessarily. • Enable logging: Keeping an eye on events like 
user_input_transcribed
and 
speech_created
can help confirm that user input is being detected as expected. If you’d like, I’d be happy to assist you in reviewing your agent’s configuration or code to help pinpoint the exact cause. Just let me know! Sources: basics/interrupts_user.py | Agent speech and audio | LiveKit Docs | How to Handle Speech Interruptions More Naturally | livekit-agents/livekit/agents/voice/agent_activity.py | LiveKit Docs
c
how to configure what the agent must say on entering the call? How to make sure the agent says the first line?
t
I'd love to help you set up what the agent says when entering a call, so it confidently delivers that first line. Here's a simple way to do it: • Use the 
on_enter()
method: This gets triggered as soon as the agent joins the room. For example:
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class CustomAgent(Agent):
    async def on_enter(self):
        await self.session.say("Hi there! How can I help you today?")
• If you're not using a custom agent, you can call 
session.say()
right after starting the session:
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await session.start(agent=agent, room=ctx.room)
await agent.say("Hello! How can I assist you?")
• For telephony agents: You can use 
session.say()
or 
session.generate_reply()
to warmly greet the caller as soon as the call connects. • Make sure TTS is set up: The 
say()
method needs a Text-to-Speech plugin like 
openai.TTS()
or 
cartesia.TTS()
to work properly. These steps will help your agent smoothly deliver that important first line. If you'd like, I'm here to walk you through the implementation—just let me know! Sources: docs/index.yaml | delay-handling/agent.py | agent.py | Agent speech and audio | LiveKit Docs | Voice Assistant Applications | livekit/livekit_composite | DeepWiki
c
difference between generate_reply and say?
t
Hi there! I’d love to help you understand the say and generate_reply methods in LiveKit—they both let the agent speak, but they each have their own special role: • say: This one’s great for delivering predefined messages. It simply turns the text you give it into speech using the Text-to-Speech (TTS) plugin you’ve set up. Think of it as perfect for fixed phrases like greetings or instructions. Here’s a quick example:
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await session.say("Hello! How can I assist you today?")
• generate_reply: This method is a bit more dynamic. It uses the Language Model (LLM) to craft responses based on what the user says or specific instructions you provide. It’s fantastic for interactive, context-aware conversations. For example:
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await session.generate_reply(user_input="What are the store hours?", instructions="Answer the user's question.")
Here’s a quick rundown of their key differences: • say: Sends out fixed messages, doesn’t use the LLM, and needs a TTS plugin to work. • generate_reply: Creates dynamic, real-time responses with the help of the LLM—perfect for engaging conversations. Both methods give you a 
SpeechHandle
, which helps you keep track of the speech and even handle interruptions smoothly. If anything’s unclear or you want to dive deeper, just let me know—I’m here to help! Sources: moviefone/README.mdoc | Realtime model plugins | LiveKit Docs | Events and error handling | LiveKit Docs | Agent speech and audio | LiveKit Docs | livekit-agents/livekit/agents/voice/agent_activity.py
c
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async def on_enter(self) -> None:
        greeting_time = "morning"
        salutation = "Mr."
        customer_name = "John"
        await self.session.say(instructions=f"Good {greeting_time}, am I speaking with {salutation} {customer_name}?")
The agent is not speaking this line on start of call, what to do?
t
Let's work together to figure out why the agent isn't speaking the line in the 
on_enter
method. Could you please check a few things for me? • Is the 
on_enter
method actually being called? Adding a simple log statement can help confirm this. • Have you set up the Text-to-Speech (TTS) plugin correctly in your agent configuration? • Are there any errors or warnings showing up in the logs when the agent starts? Once we have this information, we'll be in a great position to pinpoint the issue and find the best solution for you.
c
Does generate_reply wait for user input or can it also initiate speech?
t
Just to share a helpful tip: the 
generate_reply
function doesn’t need to wait for user input and can actually start speaking on its own. When you provide 
instructions
, the agent can create a response all by itself. For instance:
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await session.generate_reply(instructions="Say hello to the user")
This can be super handy for kicking off conversations, like warmly greeting someone right at the beginning of a session. If you'd like, I’m here to walk you through more examples or clarify anything—just let me know! Sources: Agent speech and audio | LiveKit Docs | livekit-agents/livekit/agents/voice/agent_session.py
c
In my case the on_enter function is called, _`await self.session.say(f"Good {greeting_time}, am I speaking with {salutation} {customer_name}?")`_ does produce the speech but 
await
 
_self_.session.generate_reply(_instructions_=f"Good {greeting_time}, am I speaking with {salutation} {customer_name}?")
doesn't produce any speech and directly sent to the next sent of instructions
t
I'd love to help you figure out why 
generate_reply
isn’t producing speech for you. Could you please check a few things for me? • Is the Text-to-Speech (TTS) plugin set up correctly in your agent configuration? • Have you noticed any errors or warnings in the logs when 
generate_reply
runs? • Are you working with a realtime model or a pipeline-based agent? Once we have these details, we can work together to find the best solution for you.
c
Copy code
session = AgentSession(
    #     # A Large Language Model (LLM) is your agent's brain, processing user input and generating a response
    #     # See all providers at <https://docs.livekit.io/agents/integrations/llm/>
    #     # llm=openai.LLM(model="gpt-4o-mini"),
        llm=google.LLM(model="gemini-2.5-flash-lite"),
    #     # Speech-to-text (STT) is your agent's ears, turning the user's speech into text that the LLM can understand
    #     # See all providers at <https://docs.livekit.io/agents/integrations/stt/>
        stt=elevenlabs.STT(),
    #     # Text-to-speech (TTS) is your agent's voice, turning the LLM's text into speech that the user can hear
    #     # See all providers at <https://docs.livekit.io/agents/integrations/tts/>
        tts=elevenlabs.TTS(
                model="eleven_flash_v2_5", 
                voice_id="H8bdWZHK2OgZwTN7ponr",
                voice_settings=elevenlabs.VoiceSettings(
                    stability=0.5,
                    similarity_boost=0.7,
                    speed=1.10,
                ),
                streaming_latency=4
                ),
    #     # VAD and turn detection are used to determine when the user is speaking and when the agent should respond
    #     # See more at <https://docs.livekit.io/agents/build/turns>
        turn_detection=MultilingualModel(),
        vad=ctx.proc.userdata["vad"],
    #     # allow the LLM to generate a response while waiting for the end of turn
    #     # See more at <https://docs.livekit.io/agents/build/audio/#preemptive-generation>
        preemptive_generation=True,
    )
This is my agent setup
t
Your agent setup with Google LLM (Gemini 2.5 Flash Lite) and ElevenLabs TTS is compatible with LiveKit, and 
generate_reply
should work smoothly with this configuration. If you’re finding that 
generate_reply
isn’t producing speech, don’t worry—let’s explore a few common reasons and easy fixes together: • LLM Response: It’s a good idea to check if the LLM is generating a valid response. You can try logging the output of 
generate_reply
to see what’s coming through. • TTS Configuration: Double-check that the ElevenLabs TTS plugin is set up correctly and able to turn text into speech without any hiccups. • Preemptive Generation: Since you have 
preemptive_generation=True
, sometimes the agent might skip speech if the LLM response takes a bit longer. You could try turning this off temporarily to see if it helps. If you’d like, I’m here to help you debug this further—just let me know! Sources: ElevenLabs TTS | LiveKit Docs | plugins/google/src/beta/realtime/realtime_api.ts | realtime/gemini_realtime_api.py | Google Gemini LLM | LiveKit Docs | livekit-plugins/livekit-plugins-google/livekit/plugins/google/llm.py
c
how to log the output? how to capture the input and outputs to the llm?
t
To help you log and capture the input and output to the LLM in LiveKit, here’s a simple approach you can follow: • Log Inputs: Just before you call 
generate_reply
, try logging the 
instructions
and 
user_input
parameters. For example:
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instructions = f"Good {greeting_time}, am I speaking with {salutation} {customer_name}?"
user_input = None  # If applicable
print(f"LLM Input - Instructions: {instructions}, User Input: {user_input}")
• Log Outputs: After you get the response from 
generate_reply
, don’t forget to log it as well:
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response = await self.session.generate_reply(instructions=instructions, user_input=user_input)
print(f"LLM Output: {response}")
• Enable Debug Logging: If your LiveKit setup supports it, turning on debug logging can be really helpful to capture detailed logs of LLM interactions. Following these steps should make it easier for you to check the inputs and outputs and spot any issues. If you run into any trouble or have more questions, I’m here to help!
c
while using calling the on_enter function to start a initial speech, how to handle if the speech is interrupted? Can I replay the same speech? Or add some intelligent handler?
t
Handling interruptions during the initial speech in the 
on_enter
function can feel a bit tricky, but don’t worry—I’m here to guide you through some helpful strategies: • Replay the Speech: You can use the 
SpeechHandle
returned by 
say
or 
generate_reply
to check if the speech was interrupted and then replay it if needed. Here’s a simple example:
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handle = await self.session.say("Good morning, am I speaking with Mr. John?")
if handle.interrupted:
    await self.session.say("Good morning, am I speaking with Mr. John?")
• Intelligent Handling: Another approach is to add some logic that looks at the context or the user’s input after an interruption. This way, you can decide whether to replay the message or respond differently. For instance:
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handle = await self.session.say("Good morning, am I speaking with Mr. John?")
if handle.interrupted:
    user_input = await self.session.get_last_user_input()
    if not user_input:
        await self.session.say("Could you please confirm your name?")
• Custom Interruption Logic: You might also consider using the 
on_agent_state_changed
event to keep an eye on interruptions and respond dynamically. Here’s how that could look:
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@self.session.on("agent_state_changed")
async def handle_interruption(event):
    if event.new_state == "listening" and self.session.current_speech.interrupted:
        await self.session.say("Let me repeat that: Good morning, am I speaking with Mr. John?")
These methods give you some flexibility to either replay your initial message or handle interruptions thoughtfully based on what’s happening. If you’d like, I’m happy to help you explore these options further—just let me know!
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