Update app.py

app.py

@@ -1,33 +1,22 @@
-
-
-# Install transformers if not installed
-# !pip install transformers gradio
-
-from transformers import pipeline
 import gradio as gr
+import torch
+from transformers import pipeline
 
-# Install transformers and gradio if not installed
-import os
-os.system('pip install transformers gradio')
-
-
-
-# Load a pre-trained TTS pipeline
-tts_pipeline = pipeline("text-to-speech", model="facebook/fastspeech2-en-ljspeech")
+# Hugging Face TTS 모델 로드 (불가리아어 모델로 변경 필요)
+tts = pipeline(task="text-to-speech", model="facebook/mms-tts-bul", device=0 if torch.cuda.is_available() else -1)
 
-# Function to convert text to audio using the Hugging Face TTS model
-def text_to_audio(mytext):
-    audio = tts_pipeline(mytext)  # Generate audio
-    return audio["filename"]  # Return the filename of the generated audio
+# TTS 변환 함수
+def tts_generate(text):
+    audio = tts(text, return_tensors=True)
+    return (audio['speech'].numpy(), 22050)  # 반환할 샘플링 속도와 오디오 데이터
 
-# Create a Gradio interface
-iface = gr.Interface(
-    fn=text_to_audio,
-    inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
-    outputs=gr.Audio(type="file"),  # Gradio expects a file for audio output
-    title="Text to Speech Application",
-    description="Type your text and generate the corresponding audio."
-)
+# Gradio 인터페이스 생성
+iface = gr.Interface(fn=tts_generate, 
+                     inputs="text", 
+                     outputs="audio",
+                     title="Bulgarian TTS Generator",
+                     description="Enter text to generate speech in Bulgarian.")
 
-# Launch the interface
-iface.launch(share=True)
+# 인터페이스 실행
+if __name__ == "__main__":
+    iface.launch()