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fix: migrate from custom audio recorder to native AudioBuffer (#115)

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* fix: update to pipecat VM Detector

* fix: refactor to remove audio synchronizer

* feat: add speechmatics as STT
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Abhishek 2026-01-08 18:03:26 +05:30 • committed by GitHub
parent 31521008cf
commit edf0fa4fbc
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12 changed files with 193 additions and 591 deletions
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50
api/services/pipecat/pipeline_builder.py
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@ -10,8 +10,7 @@ from api.services.pipecat.audio_config import AudioConfig
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.audio.audio_buffer_processor import AudioBuffer
from pipecat.processors.audio.audio_synchronizer import AudioSynchronizer
from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor
from pipecat.processors.transcript_processor import TranscriptProcessor
from pipecat.utils.context import turn_var
@ -23,15 +22,8 @@ def create_pipeline_components(audio_config: AudioConfig, engine: "PipecatEngine
"""Create and return the main pipeline components with proper audio configuration"""
logger.info(f"Creating pipeline components with audio config: {audio_config}")
# Use new split audio buffer for better performance
audio_buffer = AudioBuffer(
sample_rate=audio_config.pipeline_sample_rate,
buffer_size=audio_config.buffer_size_bytes,
max_recording_bytes=audio_config.max_recording_bytes,
)
# Create synchronizer for merged audio (outside pipeline)
audio_synchronizer = AudioSynchronizer(
# Use native AudioBufferProcessor for merged audio recording
audio_buffer = AudioBufferProcessor(
sample_rate=audio_config.pipeline_sample_rate,
buffer_size=audio_config.buffer_size_bytes,
)
@ -42,7 +34,7 @@ def create_pipeline_components(audio_config: AudioConfig, engine: "PipecatEngine
context = LLMContext()
return audio_buffer, audio_synchronizer, transcript, context
return audio_buffer, transcript, context
def build_pipeline(
@ -50,7 +42,6 @@ def build_pipeline(
stt,
transcript,
audio_buffer,
audio_synchronizer,
llm,
tts,
user_context_aggregator,
@ -59,30 +50,41 @@ def build_pipeline(
stt_mute_filter,
pipeline_metrics_aggregator,
user_idle_disconnect,
voicemail_detector=None,
):
"""Build the main pipeline with all components"""
# Register processors with synchronizer for merged audio
logger.info("Registering audio buffer processors with synchronizer")
audio_synchronizer.register_processors(audio_buffer.input(), audio_buffer.output())
"""Build the main pipeline with all components.
# Build processors list with optional context controller
Args:
audio_buffer: AudioBufferProcessor that handles both input and output audio recording.
voicemail_detector: Optional native pipecat VoicemailDetector. When provided,
inserts voicemail detection after STT. Note: We don't use the TTS gate
to avoid blocking TTS frames during classification.
"""
# Build processors list with optional voicemail detection
processors = [
transport.input(), # Transport user input
audio_buffer.input(), # Record input audio (only processes InputAudioRawFrame)
stt, # STT can now have audio_passthrough=False
stt_mute_filter, # STTMuteFilters don't let VAD related events pass through if muted
user_idle_disconnect,
transcript.user(),
stt, # STT (audio_passthrough=True by default, passes InputAudioRawFrame)
]
# Insert voicemail detector after STT if enabled
# Note: We intentionally do NOT use voicemail_detector.gate() to allow TTS
# frames to continue flowing during classification (non-blocking detection)
if voicemail_detector:
logger.info("Adding native voicemail detector to pipeline")
processors.append(voicemail_detector.detector())
# Continue with the rest of the pipeline
processors.extend(
[
stt_mute_filter, # STTMuteFilters don't let VAD related events pass through if muted
user_idle_disconnect,
transcript.user(),
user_context_aggregator,
llm, # LLM
pipeline_engine_callback_processor,
tts, # TTS
transport.output(), # Transport bot output
audio_buffer.output(), # Record output audio (only processes OutputAudioRawFrame)
audio_buffer, # AudioBufferProcessor - records both input and output audio
transcript.assistant(),
assistant_context_aggregator, # Assistant spoken responses
pipeline_metrics_aggregator,