does livekit have audio to audio latency

Thanks for reaching out, Rashmi. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

I meant to ask, how to expose audio to audio latency for my python live kit agent which uses openai realtime

Hey there! If you want to check out the audio-to-audio latency for your Python LiveKit agent using OpenAI Realtime, here are some friendly ways to do it: 1. Using Event Listeners for Latency Tracking: You can keep an eye on latency by listening to certain events that the session sends out:

import time
from livekit.agents import MultimodalAgent, AutoSubscribe, JobContext
from livekit.plugins.openai.realtime import RealtimeModel

class LatencyTrackingAgent:
    def __init__(self):
        self.audio_input_timestamp = None
        self.first_audio_output_timestamp = None
        self.latency_measurements = []
        
    async def setup_agent(self, ctx: JobContext):
        model = RealtimeModel()
        session = model.session()
        
        # Keep track of when audio input gets committed
        @session.on("openai_client_event_queued")
        def on_client_event(event):
            if event.get("type") == "input_audio_buffer.commit":
                self.audio_input_timestamp = time.time()
                
        # Keep track of when the first audio response comes through
        @session.on("openai_server_event_received") 
        def on_server_event(event):
            if event.get("type") == "response.audio.delta":
                if self.first_audio_output_timestamp is None:
                    self.first_audio_output_timestamp = time.time()
                    if self.audio_input_timestamp:
                        latency = self.first_audio_output_timestamp - self.audio_input_timestamp
                        self.latency_measurements.append(latency)
                        print(f"Audio-to-audio latency: {latency*1000:.2f}ms")
                        
        return session

2. Accessing Internal Timing Data: You can also peek inside the response generation objects to grab timing info and calculate how long processing takes:

async def track_response_latency(session):
    # Check if there's a current generation object
    if hasattr(session, '_current_generation') and session._current_generation:
        generation = session._current_generation
        if generation._first_token_timestamp and generation._created_timestamp:
            processing_latency = generation._first_token_timestamp - generation._created_timestamp
            print(f"Model processing latency: {processing_latency*1000:.2f}ms")

3. End-to-End Latency Measurement: If you want the full picture from audio input all the way to output, try this:

class ComprehensiveLatencyTracker:
    def __init__(self):
        self.input_start_time = None
        self.commit_time = None
        self.response_start_time = None
        self.first_audio_time = None
        
    def track_input_audio_buffer_events(self, session):
        @session.on("openai_client_event_queued")
        def on_client_event(event):
            event_type = event.get("type")
            if event_type == "input_audio_buffer.append" and self.input_start_time is None:
                self.input_start_time = time.time()
            elif event_type == "input_audio_buffer.commit":
                self.commit_time = time.time()
                
        @session.on("openai_server_event_received")
        def on_server_event(event):
            event_type = event.get("type")
            if event_type == "response.created":
                self.response_start_time = time.time()
            elif event_type == "response.audio.delta" and self.first_audio_time is None:
                self.first_audio_time = time.time()
                self.calculate_latencies()
                
    def calculate_latencies(self):
        if all([self.input_start_time, self.commit_time, self.response_start_time, self.first_audio_time]):
            input_to_commit = (self.commit_time - self.input_start_time) * 1000
            commit_to_response = (self.response_start_time - self.commit_time) * 1000  
            response_to_audio = (self.first_audio_time - self.response_start_time) * 1000
            total_latency = (self.first_audio_time - self.input_start_time) * 1000
            
            print(f"Input buffering: {input_to_commit:.2f}ms")
            print(f"Processing latency: {commit_to_response:.2f}ms") 
            print(f"Audio generation: {response_to_audio:.2f}ms")
            print(f"Total audio-to-audio latency: {total_latency:.2f}ms")

Hopefully, these tips help you measure and fine-tune latency throughout your audio pipeline. If you have any questions or want to dive deeper, just let me know—I'm here to help!