Merge pull request #316 from pipecat-ai/aleix/metrics-improvements
metrics improvements
This commit is contained in:
10
CHANGELOG.md
10
CHANGELOG.md
@@ -7,11 +7,19 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## [Unrelease]
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### Added
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- Added `send_initial_empty_metrics` flag to `PipelineParams` to request for
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initial empty metrics (zero values). True by default.
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### Fixed
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- Fixed initial metrics format. It was using the wrong keys name/time instead of
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processor/value.
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- STT services should be using ISO 8601 time format for transcription frames.
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- Fix an issue that would cause Daily transport to show a stop transcription
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- Fixed an issue that would cause Daily transport to show a stop transcription
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error when actually none occurred.
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## [0.0.37] - 2024-07-22
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@@ -64,7 +64,7 @@ class Pipeline(BasePipeline):
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services = []
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for p in self._processors:
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if isinstance(p, BasePipeline):
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services += p.processors_with_metrics()
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services.extend(p.processors_with_metrics())
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elif p.can_generate_metrics():
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services.append(p)
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return services
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@@ -21,6 +21,7 @@ from loguru import logger
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class PipelineParams(BaseModel):
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allow_interruptions: bool = False
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enable_metrics: bool = False
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send_initial_empty_metrics: bool = True
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report_only_initial_ttfb: bool = False
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@@ -95,8 +96,8 @@ class PipelineTask:
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def _initial_metrics_frame(self) -> MetricsFrame:
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processors = self._pipeline.processors_with_metrics()
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ttfb = [{"name": p.name, "time": 0.0} for p in processors]
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processing = [{"name": p.name, "time": 0.0} for p in processors]
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ttfb = [{"processor": p.name, "value": 0.0} for p in processors]
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processing = [{"processor": p.name, "value": 0.0} for p in processors]
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return MetricsFrame(ttfb=ttfb, processing=processing)
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async def _process_down_queue(self):
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@@ -106,7 +107,9 @@ class PipelineTask:
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report_only_initial_ttfb=self._params.report_only_initial_ttfb
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)
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await self._source.process_frame(start_frame, FrameDirection.DOWNSTREAM)
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await self._source.process_frame(self._initial_metrics_frame(), FrameDirection.DOWNSTREAM)
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if self._params.send_initial_empty_metrics:
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await self._source.process_frame(self._initial_metrics_frame(), FrameDirection.DOWNSTREAM)
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running = True
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should_cleanup = True
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@@ -19,6 +19,7 @@ from pipecat.frames.frames import (
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LLMMessagesAppendFrame,
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LLMMessagesUpdateFrame,
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LLMModelUpdateFrame,
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MetricsFrame,
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StartFrame,
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SystemFrame,
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TTSSpeakFrame,
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@@ -456,6 +457,13 @@ class RTVIProcessor(FrameProcessor):
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start_frame = dataclasses.replace(self._start_frame)
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await self.push_frame(start_frame)
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# Send new initial metrics with the new processors
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processors = parent.processors_with_metrics()
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processors.extend(self._pipeline.processors_with_metrics())
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ttfb = [{"processor": p.name, "value": 0.0} for p in processors]
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processing = [{"processor": p.name, "value": 0.0} for p in processors]
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await self.push_frame(MetricsFrame(ttfb=ttfb, processing=processing))
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message = RTVIBotReady()
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frame = TransportMessageFrame(message=message.model_dump(exclude_none=True))
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await self.push_frame(frame)
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@@ -678,12 +678,15 @@ class DailyOutputTransport(BaseOutputTransport):
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await self._client.send_message(frame)
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async def send_metrics(self, frame: MetricsFrame):
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metrics = {}
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if frame.ttfb:
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metrics["ttfb"] = frame.ttfb
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if frame.processing:
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metrics["processing"] = frame.processing
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message = DailyTransportMessageFrame(message={
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"type": "pipecat-metrics",
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"metrics": {
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"ttfb": frame.ttfb or [],
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"processing": frame.processing or [],
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},
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"metrics": metrics
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})
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await self._client.send_message(message)
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