@millions-hair-24956 user not able publish track in room

To troubleshoot the issue of a user not being able to publish a track in a LiveKit room, consider the following steps: 1. Check Permissions: Ensure that the participant's token has the necessary permissions to publish tracks. According to the TrackPublishException class, a common reason for failure is the lack of track publish permission. 2. Network Conditions: Verify that the network conditions are stable, as poor network conditions can also prevent track publishing. 3. Track Already Exists: If the track is already published, attempting to publish it again will throw an exception. Ensure that the track is not already published before attempting to publish it again. 4. Use Default Methods: For simplicity, use methods like

setMicrophoneEnabled

or

setCameraEnabled

to enable tracks, as they handle common cases and permissions automatically (Handling common track types). Would you like more detailed guidance on any of these steps? Sources: - TrackPublishException class - Handling common track types 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@millions-hair-24956 I facing the issue in multimodel pipeline

Could you please provide more details about the issue you're facing with the Multimodal pipeline? Specifically, it would be helpful to know: 1. Error Messages: Are there any specific error messages or logs that you are encountering? 2. Configuration: What is your current setup or configuration for the Multimodal pipeline? 3. Expected vs. Actual Behavior: What behavior are you expecting, and what are you actually experiencing? 4. Steps to Reproduce: Can you provide the steps to reproduce the issue? These details will help in diagnosing the problem more effectively. Additionally, you can refer to the MultimodalAgent documentation for more information on setup and usage. Sources: - MultimodalAgent documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@millions-hair-24956 from future import annotations import logging from dotenv import load_dotenv from livekit import rtc from livekit.agents import ( AutoSubscribe, JobContext, WorkerOptions, cli, llm, ) from livekit.agents.multimodal import MultimodalAgent from livekit.plugins import openai load_dotenv(dotenv_path=".env.example") logger = logging.getLogger("my-worker") logger.setLevel(logging.INFO) async def entrypoint(ctx: JobContext): logger.info(f"connecting to room {ctx.room.name}") await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY) participant = await ctx.wait_for_participant() run_multimodal_agent(ctx, participant) logger.info("agent started") def run_multimodal_agent(ctx: JobContext, participant: rtc.RemoteParticipant): logger.info("starting multimodal agent") model2 = openai.realtime.RealtimeModel( instructions=( "You are a voice assistant created by LiveKit. Your interface with users will be voice. " "You should use short and concise responses, and avoiding usage of unpronouncable punctuation. " "You were created as a demo to showcase the capabilities of LiveKit's agents framework." ), voice='shimmer', turn_detection=openai.realtime.ServerVadOptions( threshold=0.8, prefix_padding_ms=300, silence_duration_ms=200 ), temperature=0.7, modalities=["audio", "text"], ) model = openai.realtime.RealtimeModel( instructions=( "You are a voice assistant created by LiveKit. Your interface with users will be voice. " "You should use short and concise responses, and avoiding usage of unpronouncable punctuation. " "You were created as a demo to showcase the capabilities of LiveKit's agents framework." ), modalities=["audio", "text"], ) # create a chat context with chat history, these will be synchronized with the server # upon session establishment chat_ctx = llm.ChatContext() chat_ctx.append( text="Context about the user: you are talking to a software engineer who's building voice AI applications." "Greet the user with a friendly greeting and ask how you can help them today.", role="assistant", ) agent = MultimodalAgent( model=model2, chat_ctx=chat_ctx, ) agent.start(ctx.room, participant) # to enable the agent to speak first if name == "__main__": cli.run_app( WorkerOptions( entrypoint_fnc=entrypoint, ) ) this is m setup when i call phone number.agent attend and speak first welcome message but. i can't commit any audio

It seems like you're trying to set up a MultimodalAgent with LiveKit to handle voice interactions, but you're facing issues with committing audio after the initial welcome message. Here are a few things to check and consider: 1. Audio Track Subscription: Ensure that the audio tracks are being subscribed to correctly. The agent should be able to receive and process audio from the participant. Verify that the participant's audio track is being subscribed to and that the agent is set up to listen for incoming audio. 2. Voice Activity Detection (VAD): Check the VAD settings in your

RealtimeModel

. The

threshold

,

prefix_padding_ms

, and

silence_duration_ms

parameters should be configured to accurately detect when the participant is speaking. Adjust these settings if necessary to improve detection. 3. Event Handling: Make sure that the agent is set up to handle events such as

user_started_speaking

and

user_stopped_speaking

. These events can help manage the flow of conversation and ensure that the agent responds appropriately. 4. Debugging Logs: Enable detailed logging to capture more information about the interaction. This can help identify where the process might be failing. Look for logs related to track subscription, VAD events, and any errors that might occur during the session. 5. Session Management: Ensure that the session is being managed correctly, and that the agent is not prematurely ending the session or missing audio input due to session mismanagement. If you need more detailed guidance on any of these points, please let me know. Sources: - https://docs.livekit.io/python/livekit/agents/pipeline/human_input.html#livekit.agents.pipeline.human_input.HumanInput - https://docs.livekit.io/client-sdk-js/#md%3Aaudio-playback 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@millions-hair-24956 how to do this can you give a code for this

To address the issue of committing audio after the initial welcome message, you can ensure that the MultimodalAgent is correctly set up to handle audio input and output. Below is a code snippet that demonstrates how to configure the agent to listen for audio and respond appropriately:

from __future__ import annotations

import logging
from dotenv import load_dotenv

from livekit import rtc
from livekit.agents import (
    AutoSubscribe,
    JobContext,
    WorkerOptions,
    cli,
    llm,
)
from livekit.agents.multimodal import MultimodalAgent
from livekit.plugins import openai

load_dotenv(dotenv_path=".env.example")
logger = logging.getLogger("my-worker")
logger.setLevel(logging.INFO)

async def entrypoint(ctx: JobContext):
    logger.info(f"connecting to room {ctx.room.name}")
    await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)

    participant = await ctx.wait_for_participant()

    run_multimodal_agent(ctx, participant)

    logger.info("agent started")

def run_multimodal_agent(ctx: JobContext, participant: rtc.RemoteParticipant):
    logger.info("starting multimodal agent")

    model = openai.realtime.RealtimeModel(
        instructions=(
            "You are a voice assistant created by LiveKit. Your interface with users will be voice. "
            "You should use short and concise responses, and avoiding usage of unpronouncable punctuation. "
            "You were created as a demo to showcase the capabilities of LiveKit's agents framework."
        ),
        voice='shimmer',
        turn_detection=openai.realtime.ServerVadOptions(
            threshold=0.8, prefix_padding_ms=300, silence_duration_ms=200
        ),
        temperature=0.7,
        modalities=["audio", "text"],
    )

    chat_ctx = llm.ChatContext()
    chat_ctx.append(
        text="Context about the user: you are talking to a software engineer who's building voice AI applications."
        "Greet the user with a friendly greeting and ask how you can help them today.",
        role="assistant",
    )

    agent = MultimodalAgent(
        model=model,
        chat_ctx=chat_ctx,
    )
    agent.start(ctx.room, participant)

    # Ensure the agent is listening for audio input
    @agent.on("user_started_speaking")
    async def on_user_started_speaking():
        logger.info("User started speaking")

    @agent.on("user_stopped_speaking")
    async def on_user_stopped_speaking():
        logger.info("User stopped speaking")
        # Process the user's speech and generate a response
        await agent.process_speech()

if __name__ == "__main__":
    cli.run_app(
        WorkerOptions(
            entrypoint_fnc=entrypoint,
        )
    )