Source code for pipecat.metrics.metrics

from typing import Optional

from pydantic import BaseModel


[docs] class MetricsData(BaseModel): processor: str model: Optional[str] = None
[docs] class TTFBMetricsData(MetricsData): value: float
[docs] class ProcessingMetricsData(MetricsData): value: float
[docs] class LLMTokenUsage(BaseModel): prompt_tokens: int completion_tokens: int total_tokens: int cache_read_input_tokens: Optional[int] = None cache_creation_input_tokens: Optional[int] = None
[docs] class LLMUsageMetricsData(MetricsData): value: LLMTokenUsage
[docs] class TTSUsageMetricsData(MetricsData): value: int
[docs] class SmartTurnMetricsData(MetricsData): """Metrics data for smart turn predictions.""" is_complete: bool probability: float inference_time_ms: float server_total_time_ms: float e2e_processing_time_ms: float