Files
pipecat/src/dailyai/services/whisper_ai_services.py
2024-02-08 08:15:28 -05:00

56 lines
1.8 KiB
Python

"""This module implements Whisper transcription with a locally-downloaded model."""
import asyncio
from enum import Enum
import logging
from typing import BinaryIO
from faster_whisper import WhisperModel
from dailyai.services.local_stt_service import LocalSTTService
class Model(Enum):
"""Class of basic Whisper model selection options"""
TINY = "tiny"
BASE = "base"
MEDIUM = "medium"
LARGE = "large-v3"
DISTIL_LARGE_V2 = "Systran/faster-distil-whisper-large-v2"
DISTIL_MEDIUM_EN = "Systran/faster-distil-whisper-medium.en"
class WhisperSTTService(LocalSTTService):
"""Class to transcribe audio with a locally-downloaded Whisper model"""
_model: WhisperModel
# Model configuration
_model_name: Model
_device: str
_compute_type: str
def __init__(self, model_name: Model = Model.DISTIL_MEDIUM_EN,
device: str = "auto",
compute_type: str = "default"):
super().__init__()
self.logger: logging.Logger = logging.getLogger("dailyai")
self._model_name = model_name
self._device = device
self._compute_type = compute_type
self._load()
def _load(self):
"""Loads the Whisper model. Note that if this is the first time
this model is being run, it will take time to download."""
model = WhisperModel(
self._model_name.value,
device=self._device,
compute_type=self._compute_type)
self._model = model
async def run_stt(self, audio: BinaryIO) -> str:
"""Transcribes given audio using Whisper"""
segments, _ = await asyncio.to_thread(self._model.transcribe, audio)
res: str = ""
for segment in segments:
res += f"{segment.text} "
return res