o is@s|dZddlmZmZmZddlmZddlmZddl m Z m Z m Z m Z mZmZmZmZddlmZmZGdddeZd S) zMetrics logging observer for Pipecat. This module provides an observer that logs metrics frames to the console, allowing developers to monitor performance metrics, token usage, and other statistics in real-time. )OptionalSetType)logger) MetricsFrame) LLMTokenUsageLLMUsageMetricsData MetricsDataProcessingMetricsDataSmartTurnMetricsDataTTFBMetricsDataTTSUsageMetricsDataTurnMetricsData) BaseObserver FramePushedcseZdZdZ ddeeeeffdd Zde fddZ d ed e fd d Z d ed e fddZd ededed e fddZd ededed e fddZZS)MetricsLogObservera{Observer to log metrics activity to the console. Monitors and logs all MetricsFrame instances, including: - TTFBMetricsData (Time To First Byte) - ProcessingMetricsData (General processing time) - LLMUsageMetricsData (Token usage statistics) - TTSUsageMetricsData (Text-to-Speech character counts) - TurnMetricsData (Turn prediction metrics) This allows developers to track performance metrics, token usage, and other statistics throughout the pipeline. Examples: Log all metrics types:: observers = [MetricsLogObserver()] Log only LLM and TTS metrics:: from pipecat.metrics.metrics import LLMUsageMetricsData, TTSUsageMetricsData observers = [ MetricsLogObserver( include_metrics={LLMUsageMetricsData, TTSUsageMetricsData} ) ] Ninclude_metricsc sXtjdi||r#t|vr#ddl}|jdtdd|ththB}||_t|_ dS)a%Initialize the metrics log observer. Args: include_metrics: Set of metrics types to include. If specified, only these metrics types will be logged. If None, all metrics are logged. **kwargs: Additional arguments passed to parent class. rNzSSmartTurnMetricsData is deprecated in include_metrics, use TurnMetricsData instead.) stacklevel) super__init__r warningswarnDeprecationWarningr_include_metricsset _frames_seen)selfrkwargsr __class__rb/home/ubuntu/.local/lib/python3.10/site-packages/pipecat/observers/loggers/metrics_log_observer.pyr=s  zMetricsLogObserver.__init__datacsj|j}|j}t|tsdS|j|jvrdS|j|j|d}|jD]}||s,q$| ||q$dS)a'Handle frame push events and log metrics frames. Logs MetricsFrame instances with detailed information about the metrics data, formatted appropriately for each metrics type. Args: data: Frame push event data containing source, frame, and timestamp. Niʚ;) frame timestamp isinstanceridraddr#_should_log_metrics_log_metrics_data)rr#r$r%time_sec metrics_datarrr" on_push_frameXs     z MetricsLogObserver.on_push_framer,returncCs|jdur t||jvSdS)zDetermine if a metrics data item should be logged based on filters. Args: metrics_data: The metrics data to check. Returns: True if the metrics should be logged, False otherwise. NT)rtype)rr,rrr"r)ws z&MetricsLogObserver._should_log_metricsr+c Cs.d|jd}|jrd|jdnd}t|tr.td|d|d|jd |d d dSt|trItd|d |d|jd |d d dSt|trX| ||||dSt|t rstd|d |d|jd|d d dSt|t r| ||||dStd|d|d|d|d d dS)zLog a single metrics data item. Args: metrics_data: The metrics data to log. time_sec: Timestamp in seconds. []z ()📊 z TTFB: zs at z.3fsz PROCESSING TIMEz TTS USAGEz characters at z METRICS at N) processormodelr&r rdebugvaluer r_log_llm_usager r _log_turn)rr,r+processor_info model_inforrr"r*s*        z$MetricsLogObserver._log_metrics_datar>r?c Cs|j}d|jd|jd|jg}|jdur"|d|j|jdur0|d|j|jdur>|d|jd|}t d |d |d |d |d d dS)aLog LLM token usage metrics. Args: metrics_data: The LLM usage metrics data. processor_info: Formatted processor name string. model_info: Formatted model name string. time_sec: Timestamp in seconds. zprompt: z completion: ztotal: Nz cache_read: zcache_creation: z reasoning: z, r4z LLM TOKEN USAGEr5r7.2fr6) r; prompt_tokenscompletion_tokens total_tokenscache_read_input_tokensappendcache_creation_input_tokensreasoning_tokensjoinrr:)rr,r>r?r+usagedetails usage_strrrr"r<s       z!MetricsLogObserver._log_llm_usagecCsV|jrdnd}|jdd}td|d|d|d|jd d |d |d d dS)aLog turn prediction metrics. Args: metrics_data: The turn metrics data. processor_info: Formatted processor name string. model_info: Formatted model name string. time_sec: Timestamp in seconds. COMPLETE INCOMPLETEz.1fmsr4z TURNr5z (probability: z.2%z, e2e: z) at r@r6N) is_completee2e_processing_time_msrr: probability)rr,r>r?r+ complete_stre2e_strrrr"r=szMetricsLogObserver._log_turn)N)__name__ __module__ __qualname____doc__rrrr rrr-boolr)floatr*rstrr<rr= __classcell__rrr r"r s6  'rN)rWtypingrrrlogururpipecat.frames.framesrpipecat.metrics.metricsrrr r r r r rpipecat.observers.base_observerrrrrrrr"s  (