Files
pipecat/examples/transcription/whisper-local.py
Mark Backman e719cbbe6d Reorganize examples into topic-based subfolders
Move 304 examples from a flat numbered directory into 14 descriptive
subfolders: getting-started, services (speech + function-calling),
transcription, vision, realtime, persistent-context,
context-summarization, update-settings (stt/tts/llm), turn-management,
thinking-and-mcp, transports, video-avatar, video-processing, and
features.

Strip numbered prefixes from filenames (e.g. 07c-interruptible-deepgram.py
becomes services/speech/deepgram.py) since the folder context makes them
redundant. Keep numbered prefixes only in getting-started/ where ordering
matters.

Update eval script paths and README to match the new structure.
2026-03-31 13:12:24 -04:00

63 lines
1.7 KiB
Python

#
# Copyright (c) 2024-2026, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import sys
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import Frame, TranscriptionFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.audio.vad_processor import VADProcessor
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.whisper.stt import WhisperSTTService
from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
class TranscriptionLogger(FrameProcessor):
async def process_frame(self, frame: Frame, direction: FrameDirection):
await super().process_frame(frame, direction)
if isinstance(frame, TranscriptionFrame):
print(f"Transcription: {frame.text}")
# Push all frames through
await self.push_frame(frame, direction)
async def main():
transport = LocalAudioTransport(
LocalAudioTransportParams(
audio_in_enabled=True,
)
)
stt = WhisperSTTService()
tl = TranscriptionLogger()
vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer())
pipeline = Pipeline([transport.input(), vad_processor, stt, tl])
task = PipelineTask(pipeline)
runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())