upd example
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@@ -13,7 +13,8 @@ from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
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from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
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from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.audio.vad.vad_analyzer import VADParams
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from pipecat.audio.vad.vad_analyzer import VADParams
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from pipecat.frames.frames import Frame, LLMRunFrame, TTSTextFrame, format_pts
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from pipecat.frames.frames import LLMRunFrame, TTSTextFrame
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from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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@@ -21,7 +22,6 @@ from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import (
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from pipecat.processors.aggregators.llm_response_universal import (
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LLMContextAggregatorPair,
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LLMContextAggregatorPair,
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)
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)
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from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
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from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
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from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
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from pipecat.processors.transcript_processor import TranscriptProcessor
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from pipecat.processors.transcript_processor import TranscriptProcessor
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.types import RunnerArguments
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@@ -29,6 +29,7 @@ from pipecat.runner.utils import create_transport
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService
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from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.transports.base_output import BaseOutputTransport
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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from pipecat.transports.daily.transport import DailyParams
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from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
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from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
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@@ -36,24 +37,6 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
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load_dotenv(override=True)
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load_dotenv(override=True)
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class TimestampLogger(FrameProcessor):
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"""Frame processor that logs TTSTextFrame objects with their timestamps.
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This helps verify that word timestamps are working correctly by showing
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when each word is spoken with its presentation timestamp (PTS).
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"""
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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await super().process_frame(frame, direction)
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if isinstance(frame, TTSTextFrame):
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pts_str = format_pts(frame.pts) if frame.pts else "no PTS"
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logger.info(f"🎯 Word timestamp: '{frame.text}' at {pts_str}")
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# Always push all frames through
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await self.push_frame(frame, direction)
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# We store functions so objects (e.g. SileroVADAnalyzer) don't get
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# We store functions so objects (e.g. SileroVADAnalyzer) don't get
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# instantiated. The function will be called when the desired transport gets
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# instantiated. The function will be called when the desired transport gets
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# selected.
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# selected.
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@@ -107,9 +90,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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# Add transcript processor to show timestamps in conversation history
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# Add transcript processor to show timestamps in conversation history
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transcript = TranscriptProcessor()
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transcript = TranscriptProcessor()
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# Add timestamp logger to verify word timestamps are being generated
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timestamp_logger = TimestampLogger()
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pipeline = Pipeline(
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pipeline = Pipeline(
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[
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[
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transport.input(), # Transport user input
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transport.input(), # Transport user input
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@@ -119,7 +99,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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context_aggregator.user(), # User responses
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context_aggregator.user(), # User responses
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llm, # LLM
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llm, # LLM
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tts, # TTS (HumeTTSService with word timestamps)
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tts, # TTS (HumeTTSService with word timestamps)
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timestamp_logger, # Log word timestamps for verification
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transport.output(), # Transport bot output
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transport.output(), # Transport bot output
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transcript.assistant(), # Assistant transcripts with timestamps
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transcript.assistant(), # Assistant transcripts with timestamps
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context_aggregator.assistant(), # Assistant spoken responses
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context_aggregator.assistant(), # Assistant spoken responses
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@@ -134,7 +113,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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audio_out_sample_rate=HUME_SAMPLE_RATE,
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audio_out_sample_rate=HUME_SAMPLE_RATE,
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),
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),
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idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
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idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
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observers=[RTVIObserver(rtvi)],
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observers=[
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RTVIObserver(rtvi),
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DebugLogObserver(
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frame_types={
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TTSTextFrame: (BaseOutputTransport, FrameEndpoint.DESTINATION),
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}
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),
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],
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)
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)
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@rtvi.event_handler("on_client_ready")
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@rtvi.event_handler("on_client_ready")
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@@ -152,7 +138,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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async def on_client_connected(transport, client):
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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logger.info(f"Client connected")
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logger.info(
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logger.info(
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"💡 Word timestamps are enabled! Watch for '🎯 Word timestamp' logs showing each word with its PTS."
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"💡 Word timestamps are enabled! Watch the console for TTSTextFrame logs showing each word with its PTS."
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)
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)
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# Kick off the conversation.
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# Kick off the conversation.
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messages.append({"role": "system", "content": "Please introduce yourself to the user."})
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messages.append({"role": "system", "content": "Please introduce yourself to the user."})
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