Add TurnMetricsData and e2e processing time for KrispVivaTurn

Introduce a generic TurnMetricsData class for turn detection metrics,
replacing the service-specific SmartTurnMetricsData (now deprecated).
Add end-to-end processing time measurement to KrispVivaTurn, tracking
the interval from VAD speech-to-silence transition to model threshold
crossing. Consume metrics in the strategy _handle_input_audio path
so they are pushed immediately when fresh.

examples/foundational/07p-interruptible-krisp-viva.py

@@ -31,6 +31,8 @@ from pipecat.audio.filters.krisp_viva_filter import KrispVivaFilter
 from pipecat.audio.turn.krisp_viva_turn import KrispVivaTurn
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
+from pipecat.metrics.metrics import TurnMetricsData
+from pipecat.observers.loggers.metrics_log_observer import MetricsLogObserver
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -124,6 +126,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             enable_usage_metrics=True,
         ),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        observers=[MetricsLogObserver(include_metrics={TurnMetricsData})],
     )
 
     @transport.event_handler("on_client_connected")

examples/foundational/38b-smart-turn-local.py

@@ -12,6 +12,8 @@ from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
+from pipecat.metrics.metrics import TurnMetricsData
+from pipecat.observers.loggers.metrics_log_observer import MetricsLogObserver
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -77,7 +79,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     pipeline = Pipeline(
         [
             transport.input(),  # Transport user input
-            rtvi,
             stt,
             user_aggregator,  # User responses
             llm,  # LLM
@@ -94,17 +95,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             enable_usage_metrics=True,
         ),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+        observers=[MetricsLogObserver(include_metrics={TurnMetricsData})],
     )
 
-    @task.rtvi.event_handler("on_client_ready")
-    async def on_client_ready(rtvi):
-        # Kick off the conversation
-        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([LLMRunFrame()])
-
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
+        # Kick off the conversation
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):