Update app.py

app.py

@@ -1,70 +0,0 @@
-import os
-import tempfile
-import gradio as gr
-from TTS.utils.synthesizer import Synthesizer
-from huggingface_hub import hf_hub_download
-
-# Define constants
-MODEL_INFO = [
-    ["vits-multispeaker-495586", "best_model_495586.pth", "config.json", "saillab/vits_multi_cv_15_validated_dataset/resolve/main/","speakers.pth"],
-]
-
-# # Extract model names from MODEL_INFO
-# MODEL_NAMES = [info[0] for info in MODEL_INFO]
-
-MODEL_NAMES = [
-    "vits-multispeaker-495586",
-    # Add other model names similarly...
-]
-
-MAX_TXT_LEN = 400
-TOKEN = os.getenv('HUGGING_FACE_HUB_TOKEN')
-
-# # Download models
-# for model_name, model_file, config_file, repo_name in MODEL_INFO:
-#     os.makedirs(model_name, exist_ok=True)
-#     print(f"|> Downloading: {model_name}")
-    
-#     # Use hf_hub_download to download models from private Hugging Face repositories
-#     hf_hub_download(repo_id=repo_name, filename=model_file, use_auth_token=TOKEN)
-#     hf_hub_download(repo_id=repo_name, filename=config_file, use_auth_token=TOKEN)
-
-repo_name = "saillab/vits_multi_cv_15_validated_dataset"
-filename = "best_model_495586.pth"
-
-model_file = hf_hub_download(repo_name, filename, use_auth_token=TOKEN)
-config_file = hf_hub_download(repo_name, "config.json", use_auth_token=TOKEN)
-
-
-def synthesize(text: str, model_name: str) -> str:
-    """Synthesize speech using the selected model."""
-    if len(text) > MAX_TXT_LEN:
-        text = text[:MAX_TXT_LEN]
-        print(f"Input text was cut off as it exceeded the {MAX_TXT_LEN} character limit.")
-    
-    synthesizer = Synthesizer(model_file, config_file)
-    if synthesizer is None:
-        raise NameError("Model not found")
-    
-    wavs = synthesizer.tts(text)
-    
-    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
-        synthesizer.save_wav(wavs, fp)
-        return fp.name
-
-
-iface = gr.Interface(
-    fn=synthesize,
-    inputs=[
-        gr.Textbox(label="Enter Text to Synthesize:", value="زین همرهان سست عناصر، دلم گرفت."),
-        gr.Radio(label="Pick a Model", choices=MODEL_NAMES, value=MODEL_NAMES[0]),
-    ],
-    outputs=gr.Audio(label="Output", type='filepath'),
-    examples=[["زین همرهان سست عناصر، دلم گرفت.", MODEL_NAMES[0]]],
-    title='Persian TTS Playground',
-    description="Persian text to speech model demo",
-    article="",
-    live=False
-)
-
-iface.launch()