Remove processing metrics (ProcessingMetricsData)

Processing metrics were an early addition that predated a clear
understanding of what timing measurements matter in real-time pipelines.
They were inconsistently implemented across services, often broken, and
overlapped with the better-defined TTFB metric.

- Remove ProcessingMetricsData class and all start/stop_processing_metrics
  methods from FrameProcessorMetrics, FrameProcessor, and SentryMetrics
- Remove all processing metrics calls from 31 service files (LLM, TTS,
  STT, image, vision, realtime)
- Clean up empty _start_metrics() stubs left in STT services
- Remove processing metrics handling from RTVI, metrics log observer,
  pipeline task initial metrics, and strands agents framework
- Update tests and examples

Remaining metrics (TTFB, LLM token usage, TTS character usage, text
aggregation time) are well-defined and consistently implemented.

tests/test_openai_llm_timeout.py

@@ -61,8 +61,6 @@ async def test_openai_llm_emits_error_frame_on_timeout():
         )
 
         # Mock metrics methods
-        service.start_processing_metrics = AsyncMock()
-        service.stop_processing_metrics = AsyncMock()
         service.start_ttfb_metrics = AsyncMock()
 
         # Create a context frame to process
@@ -108,8 +106,6 @@ async def test_openai_llm_timeout_still_pushes_end_frame():
         service.push_error = AsyncMock()
         service._call_event_handler = AsyncMock()
         service._process_context = AsyncMock(side_effect=httpx.TimeoutException("Timeout"))
-        service.start_processing_metrics = AsyncMock()
-        service.stop_processing_metrics = AsyncMock()
 
         context = LLMContext(
             messages=[{"role": "user", "content": "Hello"}],
@@ -123,9 +119,6 @@ async def test_openai_llm_timeout_still_pushes_end_frame():
         assert LLMFullResponseStartFrame in frame_types
         assert LLMFullResponseEndFrame in frame_types
 
-        # Verify metrics were stopped
-        service.stop_processing_metrics.assert_called_once()
-
 
 @pytest.mark.asyncio
 async def test_openai_llm_stream_closed_on_cancellation():
@@ -208,8 +201,6 @@ async def test_openai_llm_emits_error_frame_on_exception():
         service.push_error = mock_push_error
         service._call_event_handler = AsyncMock()
         service._process_context = AsyncMock(side_effect=RuntimeError("API Error"))
-        service.start_processing_metrics = AsyncMock()
-        service.stop_processing_metrics = AsyncMock()
 
         context = LLMContext(
             messages=[{"role": "user", "content": "Hello"}],