o ÿi7 ã@s°dZddlmZddlmZGdd„deƒZGdd„deƒZGdd „d eƒZGd d „d eƒZGd d „d eƒZ Gdd„deƒZ Gdd„deƒZ Gdd„deƒZ Gdd„de ƒZ dS)zÏMetrics data models for Pipecat framework. This module defines Pydantic models for various types of metrics data collected throughout the pipeline, including timing, token usage, and processing statistics. é)ÚOptional)Ú BaseModelc@s*eZdZUdZeed<dZeeed<dS)Ú MetricsDataz·Base class for all metrics data. Parameters: processor: Name of the processor generating the metrics. model: Optional model name associated with the metrics. Ú processorNÚmodel)Ú__name__Ú __module__Ú __qualname__Ú__doc__ÚstrÚ__annotations__rr©r r úK/home/ubuntu/.local/lib/python3.10/site-packages/pipecat/metrics/metrics.pyrs rc@óeZdZUdZeed<dS)ÚTTFBMetricsDataziTime To First Byte (TTFB) metrics data. Parameters: value: TTFB measurement in seconds. ÚvalueN©rrr r Úfloatr r r r rró  rc@r)ÚProcessingMetricsDatazrGeneral processing time metrics data. Parameters: value: Processing time measurement in seconds. rNrr r r rr)rrc@sZeZdZUdZeed<eed<eed<dZeeed<dZeeed<dZ eeed<dS) Ú LLMTokenUsageaÄToken usage statistics for LLM operations. Parameters: prompt_tokens: Number of tokens in the input prompt. completion_tokens: Number of tokens in the generated completion. total_tokens: Total number of tokens used (prompt + completion). cache_read_input_tokens: Number of tokens read from cache, if applicable. cache_creation_input_tokens: Number of tokens used to create cache entries, if applicable. Ú prompt_tokensÚcompletion_tokensÚ total_tokensNÚcache_read_input_tokensÚcache_creation_input_tokensÚreasoning_tokens) rrr r Úintr rrrrr r r rr3s  rc@r)ÚLLMUsageMetricsDatazpLLM token usage metrics data. Parameters: value: Token usage statistics for the LLM operation. rN)rrr r rr r r r rrFrrc@r)ÚTTSUsageMetricsDataznText-to-Speech usage metrics data. Parameters: value: Number of characters processed by TTS. rN)rrr r rr r r r rrPrrc@r)ÚTextAggregationMetricsDataaText aggregation time metrics data. Measures the time from the first LLM token to the first complete sentence, representing the latency cost of sentence aggregation in the TTS pipeline. Parameters: value: Aggregation time in seconds. rNrr r r rr Zs  r c@s*eZdZUdZeed<eed<eed<dS)ÚTurnMetricsDataaoMetrics data for turn detection predictions. Parameters: is_complete: Whether the turn is predicted to be complete. probability: Confidence probability of the turn completion prediction. e2e_processing_time_ms: End-to-end processing time in milliseconds, measured from VAD speech-to-silence transition to turn completion. Ú is_completeÚ probabilityÚe2e_processing_time_msN)rrr r Úboolr rr r r rr!gs   r!c@s*eZdZUdZdZeed<dZeed<dS)ÚSmartTurnMetricsDataaJMetrics data for smart turn predictions. .. deprecated:: 0.0.104 Use :class:`TurnMetricsData` instead. This class will be removed in a future version. Parameters: inference_time_ms: Time taken for inference in milliseconds. server_total_time_ms: Total server processing time in milliseconds. gÚinference_time_msÚserver_total_time_msN)rrr r r'rr r(r r r rr&vs  r&N)r ÚtypingrÚpydanticrrrrrrrr r!r&r r r rÚs