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43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
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import io
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from werkzeug.datastructures import FileStorage
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from core.llm.llm_builder import LLMBuilder
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from core.llm.provider.llm_provider_service import LLMProviderService
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from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
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from core.llm.whisper import Whisper
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from models.provider import ProviderName
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FILE_SIZE_LIMIT = 1 * 1024 * 1024
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ALLOWED_EXTENSIONS = ['mp3', 'mp4', 'mpeg', 'mpga', 'm4a', 'wav', 'webm']
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class AudioService:
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@classmethod
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def transcript(cls, tenant_id: str, file: FileStorage):
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if file is None:
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raise NoAudioUploadedServiceError()
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extension = file.mimetype
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if extension not in [f'audio/{ext}' for ext in ALLOWED_EXTENSIONS]:
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raise UnsupportedAudioTypeServiceError()
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file_content = file.read()
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file_size = len(file_content)
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if file_size > FILE_SIZE_LIMIT:
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message = f"({file_size} > {FILE_SIZE_LIMIT})"
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raise AudioTooLargeServiceError(message)
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provider_name = LLMBuilder.get_default_provider(tenant_id)
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if provider_name != ProviderName.OPENAI.value:
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raise ProviderNotSupportSpeechToTextServiceError('haha')
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provider_service = LLMProviderService(tenant_id, provider_name)
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buffer = io.BytesIO(file_content)
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buffer.name = 'temp.wav'
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return Whisper(provider_service.provider).transcribe(buffer)
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