Update app.py

app.py

@@ -23,22 +23,13 @@ db = get_db_firestore()
 asr = pipeline("automatic-speech-recognition", "facebook/wav2vec2-base-960h")
 
 MODEL_NAMES = [
-    # "en/ek1/tacotron2",
     "en/ljspeech/tacotron2-DDC",
-    # "en/ljspeech/tacotron2-DDC_ph",
     "en/ljspeech/glow-tts",
-    # "en/ljspeech/tacotron2-DCA",
     "en/ljspeech/speedy-speech-wn",
     "en/ljspeech/vits",
-    "en/vctk/sc-glow-tts",
-    "en/vctk/vits",
     "en/sam/tacotron-DDC",
-    # "es/mai/tacotron2-DDC",
     "fr/mai/tacotron2-DDC",
-    #"zh-CN/baker/tacotron2-DDC-GST",
-    #"nl/mai/tacotron2-DDC",
     "de/thorsten/tacotron2-DCA",
-    # "ja/kokoro/tacotron2-DDC",
 ]
 MODELS = {}
 manager = ModelManager()
@@ -89,9 +80,6 @@ def selectall(text):
     docs = db.collection('Text2SpeechSentimentSave').stream()
     doclist=''
     for doc in docs:
-        #docid=doc.id
-        #dict=doc.to_dict()
-        #doclist+=doc.to_dict()
         r=(f'{doc.id} => {doc.to_dict()}')
         doclist += r
     return doclist 
@@ -102,15 +90,12 @@ def tts(text: str, model_name: str):
     if synthesizer is None:
         raise NameError("model not found")
     wavs = synthesizer.tts(text)
-    # output = (synthesizer.output_sample_rate, np.array(wavs))
-    # return output
     with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
         synthesizer.save_wav(wavs, fp)
         return fp.name
 
 demo = gr.Blocks()
 with demo:
-    #audio_file = gr.Audio(type="filepath")
     audio_file = gr.inputs.Audio(source="microphone", type="filepath")
     text = gr.Textbox()
     label = gr.Label()