mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
124ce03bf8
* fix: impossible import error (#563) * evaluation cli - database events experiment * hallucinations * evaluation - unhallucinate * evaluation - unhallucinate * roll back reliability link * self reviewio * lint * self review * add file pipeline to cli * add file pipeline to cli + sorting * remove cli tests * remove ai comments * comments
78 lines
2.3 KiB
Python
78 lines
2.3 KiB
Python
"""
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File transcription implementation using the GPU service from modal.com
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API will be a POST request to TRANSCRIPT_URL:
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```json
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{
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"audio_file_url": "https://...",
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"language": "en",
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"model": "parakeet-tdt-0.6b-v2",
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"batch": true
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}
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```
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"""
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import httpx
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from reflector.processors.file_transcript import (
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FileTranscriptInput,
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FileTranscriptProcessor,
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)
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from reflector.processors.file_transcript_auto import FileTranscriptAutoProcessor
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from reflector.processors.types import Transcript, Word
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from reflector.settings import settings
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class FileTranscriptModalProcessor(FileTranscriptProcessor):
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def __init__(self, modal_api_key: str | None = None, **kwargs):
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super().__init__(**kwargs)
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if not settings.TRANSCRIPT_URL:
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raise Exception(
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"TRANSCRIPT_URL required to use FileTranscriptModalProcessor"
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)
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self.transcript_url = settings.TRANSCRIPT_URL
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self.file_timeout = settings.TRANSCRIPT_FILE_TIMEOUT
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self.modal_api_key = modal_api_key
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async def _transcript(self, data: FileTranscriptInput):
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"""Send full file to Modal for transcription"""
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url = f"{self.transcript_url}/v1/audio/transcriptions-from-url"
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self.logger.info(f"Starting file transcription from {data.audio_url}")
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headers = {}
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if self.modal_api_key:
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headers["Authorization"] = f"Bearer {self.modal_api_key}"
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async with httpx.AsyncClient(timeout=self.file_timeout) as client:
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response = await client.post(
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url,
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headers=headers,
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json={
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"audio_file_url": data.audio_url,
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"language": data.language,
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"batch": True,
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},
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)
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response.raise_for_status()
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result = response.json()
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words = [
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Word(
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text=word_info["word"],
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start=word_info["start"],
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end=word_info["end"],
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)
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for word_info in result.get("words", [])
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]
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# words come not in order
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words.sort(key=lambda w: w.start)
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return Transcript(words=words)
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# Register with the auto processor
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FileTranscriptAutoProcessor.register("modal", FileTranscriptModalProcessor)
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