Feat/chat support voice input (#532)

api/services/audio_service.py

@@ -0,0 +1,43 @@
+import io
+from werkzeug.datastructures import FileStorage
+from core.llm.llm_builder import LLMBuilder
+from core.llm.provider.llm_provider_service import LLMProviderService
+from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
+from core.llm.whisper import Whisper
+from models.provider import ProviderName
+
+FILE_SIZE_LIMIT = 1 * 1024 * 1024
+ALLOWED_EXTENSIONS = ['mp3', 'mp4', 'mpeg', 'mpga', 'm4a', 'wav', 'webm']
+
+class AudioService:
+    @classmethod
+    def transcript(cls, tenant_id: str, file: FileStorage):
+        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"({file_size} > {FILE_SIZE_LIMIT})"
+            raise AudioTooLargeServiceError(message)
+        
+        provider_name = LLMBuilder.get_default_provider(tenant_id)
+        if provider_name != ProviderName.OPENAI.value:
+            raise ProviderNotSupportSpeechToTextServiceError('haha')
+
+        provider_service = LLMProviderService(tenant_id, provider_name)
+
+        buffer = io.BytesIO(file_content)
+        buffer.name = 'temp.wav'
+
+        return Whisper(provider_service.provider).transcribe(buffer)
+
+
+
+        
+