@millions-hair-24956 https://docs.livekit.io/agents/build/metrics/ Are metrics available for the multimodal voice agent as well? I want to test the latency between a user stopping to speak and the agent responding back

Yes, metrics are available for the MultimodalAgent, including those that can help measure latency. According to the LiveKit documentation, you can capture metrics such as

end_of_utterance_delay

and

ttft

(time to first token) to calculate the latency between when a user stops speaking and when the agent starts responding. These metrics are part of the metrics module provided by LiveKit. Would you like more details on how to implement this or any specific code examples? Sources: - LiveKit Metrics Documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@millions-hair-24956 But it says this on the page: The following metric types are available for

VoicePipelineAgent

.

The documentation primarily highlights metrics for the

VoicePipelineAgent

, but the underlying metrics module can still be used with the

MultimodalAgent

. According to the LiveKit metrics documentation, while specific examples are given for

VoicePipelineAgent

, the metrics such as

end_of_utterance_delay

and

ttft

are generally applicable to any agent that uses the LiveKit framework, including

MultimodalAgent

. Would you like more detailed guidance on how to apply these metrics to the

MultimodalAgent

? Sources: - LiveKit Metrics Documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

Can you tell me how I can log these to another file maybe? Or in my logs itself I want to find the delay between the user stopping speaking and the agent starting to speak again (basically the time taken for agent to hear and respond back to the user). Can you suggest how to implement it @millions-hair-24956

To log metrics such as the delay between the user stopping speaking and the agent starting to speak, you can use the

metrics_collected

event in LiveKit. According to the LiveKit metrics documentation, you can subscribe to this event and use the

log_metrics

function to format and log the metrics. Here's a basic implementation: 1. Subscribe to Metrics Event: Use the

metrics_collected

event to capture metrics during a session. 2. Log Metrics: Use the

log_metrics

function to log the metrics to your desired logging system. Here's a code snippet to illustrate this:

from livekit.agents import metrics
import logging

# Set up logging
logger = logging.getLogger('metrics_logger')
handler = logging.FileHandler('metrics.log')
logger.addHandler(handler)
logger.setLevel(logging.INFO)

# Subscribe to metrics collection events
@agent.on("metrics_collected")
def on_metrics_collected(mtrcs: metrics.AgentMetrics):
    # Log the metrics using the helper function
    metrics.log_metrics(mtrcs, logger=logger)

This code sets up a logger to write to a file named

metrics.log

and logs the metrics whenever they are collected. You can adjust the logging configuration to suit your needs, such as logging to a different file or integrating with a logging service. Would you like more detailed guidance on any specific part of this process? Sources: - LiveKit Metrics Documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.