wehub-resource-sync
fed8b2eed7
Build and push multi-arch DocsGPT Docker image / build (linux/amd64, ubuntu-latest, amd64) (push) Has been cancelled
Backend release / release (push) Has been cancelled
Bandit Security Scan / bandit_scan (push) Has been cancelled
Build and push multi-arch DocsGPT Docker image / build (linux/arm64, ubuntu-24.04-arm, arm64) (push) Has been cancelled
Build and push multi-arch DocsGPT Docker image / manifest (push) Has been cancelled
Build and push DocsGPT FE Docker image for development / build (linux/amd64, ubuntu-latest, amd64) (push) Has been cancelled
Build and push DocsGPT FE Docker image for development / build (linux/arm64, ubuntu-24.04-arm, arm64) (push) Has been cancelled
Build and push DocsGPT FE Docker image for development / manifest (push) Has been cancelled
Python linting / ruff (push) Has been cancelled
Run python tests with pytest / Run tests and count coverage (3.12) (push) Has been cancelled
React Widget Build / build (push) Has been cancelled
71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
from pathlib import Path
|
|
from typing import Dict, Optional
|
|
|
|
from application.stt.base import BaseSTT
|
|
|
|
|
|
class FasterWhisperSTT(BaseSTT):
|
|
def __init__(
|
|
self,
|
|
model_size: str = "base",
|
|
device: str = "auto",
|
|
compute_type: str = "int8",
|
|
):
|
|
self.model_size = model_size
|
|
self.device = device
|
|
self.compute_type = compute_type
|
|
self._model = None
|
|
|
|
def _get_model(self):
|
|
if self._model is None:
|
|
try:
|
|
from faster_whisper import WhisperModel
|
|
except ImportError as exc:
|
|
raise ImportError(
|
|
"faster-whisper is required to use the faster_whisper STT provider."
|
|
) from exc
|
|
|
|
self._model = WhisperModel(
|
|
self.model_size,
|
|
device=self.device,
|
|
compute_type=self.compute_type,
|
|
)
|
|
return self._model
|
|
|
|
def transcribe(
|
|
self,
|
|
file_path: Path,
|
|
language: Optional[str] = None,
|
|
timestamps: bool = False,
|
|
diarize: bool = False,
|
|
) -> Dict[str, object]:
|
|
_ = diarize
|
|
model = self._get_model()
|
|
segments_iter, info = model.transcribe(
|
|
str(file_path),
|
|
language=language,
|
|
word_timestamps=timestamps,
|
|
)
|
|
|
|
segments = []
|
|
text_parts = []
|
|
for segment in segments_iter:
|
|
segment_text = getattr(segment, "text", "").strip()
|
|
if segment_text:
|
|
text_parts.append(segment_text)
|
|
segments.append(
|
|
{
|
|
"start": getattr(segment, "start", None),
|
|
"end": getattr(segment, "end", None),
|
|
"text": segment_text,
|
|
}
|
|
)
|
|
|
|
return {
|
|
"text": " ".join(text_parts).strip(),
|
|
"language": getattr(info, "language", language),
|
|
"duration_s": getattr(info, "duration", None),
|
|
"segments": segments if timestamps else [],
|
|
"provider": "faster_whisper",
|
|
}
|