mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
Mathieu Virbel
d94e2911c3
* serverless: implement banana backend for both audio and LLM Related to monadical-sas/reflector-gpu-banana project * serverless: got llm working on banana ! * tests: fixes * serverless: fix dockerfile to use fastapi server + httpx
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
from reflector.processors.audio_transcript import AudioTranscriptProcessor
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from reflector.processors.audio_transcript_auto import AudioTranscriptAutoProcessor
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from reflector.processors.types import AudioFile, Transcript, Word
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from faster_whisper import WhisperModel
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class AudioTranscriptWhisperProcessor(AudioTranscriptProcessor):
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def __init__(self):
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super().__init__()
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self.model = WhisperModel(
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"tiny", device="cpu", compute_type="float32", num_workers=12
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)
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async def _transcript(self, data: AudioFile):
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segments, _ = self.model.transcribe(
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data.path.as_posix(),
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language="en",
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beam_size=5,
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# condition_on_previous_text=True,
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word_timestamps=True,
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vad_filter=True,
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vad_parameters={"min_silence_duration_ms": 500},
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)
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if not segments:
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return
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transcript = Transcript(words=[])
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segments = list(segments)
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ts = data.timestamp
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for segment in segments:
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transcript.text += segment.text
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for word in segment.words:
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transcript.words.append(
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Word(
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text=word.word,
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start=round(ts + word.start, 3),
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end=round(ts + word.end, 3),
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)
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)
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return transcript
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AudioTranscriptAutoProcessor.register("whisper", AudioTranscriptWhisperProcessor)
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