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import io | |
from typing import Optional | |
from werkzeug.datastructures import FileStorage | |
from core.model_manager import ModelManager | |
from core.model_runtime.entities.model_entities import ModelType | |
from models.model import App, AppMode, AppModelConfig | |
from services.errors.audio import ( | |
AudioTooLargeServiceError, | |
NoAudioUploadedServiceError, | |
ProviderNotSupportSpeechToTextServiceError, | |
ProviderNotSupportTextToSpeechServiceError, | |
UnsupportedAudioTypeServiceError, | |
) | |
FILE_SIZE = 30 | |
FILE_SIZE_LIMIT = FILE_SIZE * 1024 * 1024 | |
ALLOWED_EXTENSIONS = ['mp3', 'mp4', 'mpeg', 'mpga', 'm4a', 'wav', 'webm', 'amr'] | |
class AudioService: | |
def transcript_asr(cls, app_model: App, file: FileStorage, end_user: Optional[str] = None): | |
if app_model.mode in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]: | |
workflow = app_model.workflow | |
if workflow is None: | |
raise ValueError("Speech to text is not enabled") | |
features_dict = workflow.features_dict | |
if 'speech_to_text' not in features_dict or not features_dict['speech_to_text'].get('enabled'): | |
raise ValueError("Speech to text is not enabled") | |
else: | |
app_model_config: AppModelConfig = app_model.app_model_config | |
if not app_model_config.speech_to_text_dict['enabled']: | |
raise ValueError("Speech to text is not enabled") | |
if file is None: | |
raise NoAudioUploadedServiceError() | |
extension = file.mimetype | |
if extension not in [f'audio/{ext}' for ext in ALLOWED_EXTENSIONS]: | |
raise UnsupportedAudioTypeServiceError() | |
file_content = file.read() | |
file_size = len(file_content) | |
if file_size > FILE_SIZE_LIMIT: | |
message = f"Audio size larger than {FILE_SIZE} mb" | |
raise AudioTooLargeServiceError(message) | |
model_manager = ModelManager() | |
model_instance = model_manager.get_default_model_instance( | |
tenant_id=app_model.tenant_id, | |
model_type=ModelType.SPEECH2TEXT | |
) | |
if model_instance is None: | |
raise ProviderNotSupportSpeechToTextServiceError() | |
buffer = io.BytesIO(file_content) | |
buffer.name = 'temp.mp3' | |
return {"text": model_instance.invoke_speech2text(file=buffer, user=end_user)} | |
def transcript_tts(cls, app_model: App, text: str, streaming: bool, | |
voice: Optional[str] = None, end_user: Optional[str] = None): | |
if app_model.mode in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]: | |
workflow = app_model.workflow | |
if workflow is None: | |
raise ValueError("TTS is not enabled") | |
features_dict = workflow.features_dict | |
if 'text_to_speech' not in features_dict or not features_dict['text_to_speech'].get('enabled'): | |
raise ValueError("TTS is not enabled") | |
voice = features_dict['text_to_speech'].get('voice') if voice is None else voice | |
else: | |
text_to_speech_dict = app_model.app_model_config.text_to_speech_dict | |
if not text_to_speech_dict.get('enabled'): | |
raise ValueError("TTS is not enabled") | |
voice = text_to_speech_dict.get('voice') if voice is None else voice | |
model_manager = ModelManager() | |
model_instance = model_manager.get_default_model_instance( | |
tenant_id=app_model.tenant_id, | |
model_type=ModelType.TTS | |
) | |
if model_instance is None: | |
raise ProviderNotSupportTextToSpeechServiceError() | |
try: | |
return model_instance.invoke_tts( | |
content_text=text.strip(), | |
user=end_user, | |
streaming=streaming, | |
tenant_id=app_model.tenant_id, | |
voice=voice | |
) | |
except Exception as e: | |
raise e | |
def transcript_tts_voices(cls, tenant_id: str, language: str): | |
model_manager = ModelManager() | |
model_instance = model_manager.get_default_model_instance( | |
tenant_id=tenant_id, | |
model_type=ModelType.TTS | |
) | |
if model_instance is None: | |
raise ProviderNotSupportTextToSpeechServiceError() | |
try: | |
return model_instance.get_tts_voices(language) | |
except Exception as e: | |
raise e | |