From d4ff7f06ee699e9ba6d7f4ec2dc5fa5c60add0f0 Mon Sep 17 00:00:00 2001 From: Kwindla Hultman Kramer Date: Sun, 3 Aug 2025 11:07:23 -0700 Subject: [PATCH] audio glitch test --- khk/audio-glitch.py | 185 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 185 insertions(+) create mode 100644 khk/audio-glitch.py diff --git a/khk/audio-glitch.py b/khk/audio-glitch.py new file mode 100644 index 000000000..338b44dbb --- /dev/null +++ b/khk/audio-glitch.py @@ -0,0 +1,185 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os +import time +import statistics + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams +from pipecat.transports.services.daily import DailyParams +from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor +from pipecat.processors.frame_processor import FrameProcessor, FrameDirection +from pipecat.frames.frames import Frame, TTSStartedFrame, TTSStoppedFrame, TTSAudioRawFrame +from pipecat.pipeline.parallel_pipeline import ParallelPipeline + + +load_dotenv(override=True) + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + ), +} + + +class AudioTimingProcessor(FrameProcessor): + def __init__(self, print_interval=False): + super().__init__() + self.print_interval = print_interval + self.tts_started_time = None + self.tts_stopped_time = None + self.tts_last_frame_time = None + self.tts_audio_frame_intervals = [] + self.tts_audio_frame_count = 0 + self.dummy_sum_of_intervals = 0 + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, TTSStartedFrame): + self.tts_started_time = time.time() + elif isinstance(frame, TTSAudioRawFrame): + self.tts_audio_frame_count += 1 + if self.tts_last_frame_time is not None: + self.tts_audio_frame_intervals.append(time.time() - self.tts_last_frame_time) + # tiny but pointless amount of computation + self.dummy_sum_of_intervals += time.time() - self.tts_audio_frame_intervals[-1] + sum(i * i for i in range(10000)) + + self.tts_last_frame_time = time.time() + elif isinstance(frame, TTSStoppedFrame): + self.print_intervals() + self.tts_stopped_time = time.time() + self.tts_audio_frame_count = 0 + self.tts_audio_frame_intervals = [] + + await self.push_frame(frame, direction) + + def print_intervals(self): + if not self.print_interval: + return + + # print max, min, median, audio frame count. + if self.tts_audio_frame_intervals: + logger.info(f"TTS audio frame intervals: max={max(self.tts_audio_frame_intervals):.2f}, min={min(self.tts_audio_frame_intervals):.2f}, median={statistics.median(self.tts_audio_frame_intervals):.2f}, audio frame count={self.tts_audio_frame_count}") + else: + logger.info(f"TTS audio frame intervals: no data available, audio frame count={self.tts_audio_frame_count}") + + +async def run_bot(transport: BaseTransport): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + rtvi = RTVIProcessor(config=RTVIConfig(config=[])) + + + # Create a bunch of the above simple processors to test audio frame delay glitching. + # On my machine, 200 processors causes a big problem. 100 shows just occasional very small glitches. + # Commit 061f2086b278f8df11cef73a6170d8413ef6334a is worse than current main (which makes sense). + NUM_PROCESSORS_IN_PARALLEL_PIPELINE = 200 + silent_timing_processors = [AudioTimingProcessor() for _ in range(NUM_PROCESSORS_IN_PARALLEL_PIPELINE-1)] + extra_processors = ParallelPipeline( + [AudioTimingProcessor(print_interval=True)], + [*silent_timing_processors, AudioTimingProcessor(print_interval=True)] + ) + + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = OpenAILLMContext(messages) + context_aggregator = llm.create_context_aggregator(context) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + rtvi, # RTVI processor + stt, + context_aggregator.user(), # User responses + llm, # LLM + tts, # TTS + extra_processors, + transport.output(), # Transport bot output + context_aggregator.assistant(), # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + observers=[RTVIObserver(rtvi)], + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([context_aggregator.user().get_context_frame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=False) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main()