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127 lines
4.6 KiB
Python
127 lines
4.6 KiB
Python
import io
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from typing import Optional
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from werkzeug.datastructures import FileStorage
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from core.model_manager import ModelManager
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from core.model_runtime.entities.model_entities import ModelType
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from models.model import App, AppMode, AppModelConfig
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from services.errors.audio import (
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AudioTooLargeServiceError,
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NoAudioUploadedServiceError,
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ProviderNotSupportSpeechToTextServiceError,
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ProviderNotSupportTextToSpeechServiceError,
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UnsupportedAudioTypeServiceError,
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)
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FILE_SIZE = 30
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FILE_SIZE_LIMIT = FILE_SIZE * 1024 * 1024
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ALLOWED_EXTENSIONS = ['mp3', 'mp4', 'mpeg', 'mpga', 'm4a', 'wav', 'webm', 'amr']
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class AudioService:
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@classmethod
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def transcript_asr(cls, app_model: App, file: FileStorage, end_user: Optional[str] = None):
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if app_model.mode in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]:
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workflow = app_model.workflow
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if workflow is None:
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raise ValueError("Speech to text is not enabled")
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features_dict = workflow.features_dict
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if 'speech_to_text' not in features_dict or not features_dict['speech_to_text'].get('enabled'):
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raise ValueError("Speech to text is not enabled")
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else:
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app_model_config: AppModelConfig = app_model.app_model_config
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if not app_model_config.speech_to_text_dict['enabled']:
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raise ValueError("Speech to text is not enabled")
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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"Audio size larger than {FILE_SIZE} mb"
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raise AudioTooLargeServiceError(message)
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model_manager = ModelManager()
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model_instance = model_manager.get_default_model_instance(
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tenant_id=app_model.tenant_id,
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model_type=ModelType.SPEECH2TEXT
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)
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if model_instance is None:
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raise ProviderNotSupportSpeechToTextServiceError()
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buffer = io.BytesIO(file_content)
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buffer.name = 'temp.mp3'
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return {"text": model_instance.invoke_speech2text(file=buffer, user=end_user)}
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@classmethod
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def transcript_tts(cls, app_model: App, text: str, streaming: bool,
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voice: Optional[str] = None, end_user: Optional[str] = None):
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if app_model.mode in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]:
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workflow = app_model.workflow
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if workflow is None:
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raise ValueError("TTS is not enabled")
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features_dict = workflow.features_dict
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if 'text_to_speech' not in features_dict or not features_dict['text_to_speech'].get('enabled'):
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raise ValueError("TTS is not enabled")
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voice = features_dict['text_to_speech'].get('voice') if voice is None else voice
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else:
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text_to_speech_dict = app_model.app_model_config.text_to_speech_dict
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if not text_to_speech_dict.get('enabled'):
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raise ValueError("TTS is not enabled")
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voice = text_to_speech_dict.get('voice') if voice is None else voice
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model_manager = ModelManager()
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model_instance = model_manager.get_default_model_instance(
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tenant_id=app_model.tenant_id,
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model_type=ModelType.TTS
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)
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if model_instance is None:
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raise ProviderNotSupportTextToSpeechServiceError()
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try:
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if not voice:
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voices = model_instance.get_tts_voices()
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if voices:
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voice = voices[0].get('value')
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else:
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raise ValueError("Sorry, no voice available.")
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return model_instance.invoke_tts(
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content_text=text.strip(),
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user=end_user,
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streaming=streaming,
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tenant_id=app_model.tenant_id,
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voice=voice
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)
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except Exception as e:
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raise e
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@classmethod
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def transcript_tts_voices(cls, tenant_id: str, language: str):
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model_manager = ModelManager()
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model_instance = model_manager.get_default_model_instance(
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tenant_id=tenant_id,
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model_type=ModelType.TTS
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)
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if model_instance is None:
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raise ProviderNotSupportTextToSpeechServiceError()
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try:
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return model_instance.get_tts_voices(language)
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except Exception as e:
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raise e
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