Update app.py

app.py

@@ -36,39 +36,54 @@ from TTS.utils.generic_utils import get_user_data_dir
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
 from huggingface_hub import HfApi
+import os
+from TTS.utils.manage import get_user_data_dir  # Asegúrate de importar esta función si no lo estaba
 
-# will use api to restart space on a unrecoverable error
+# Autenticación con la API de Hugging Face
 api = HfApi(token=HF_TOKEN)
-repo_id = "coqui/xtts"
+repo_id = "Blakus/XTTS_custom"
 
-# Use never ffmpeg binary for Ubuntu20 to use denoising for microphone input
-print("Export newer ffmpeg binary for denoise filter")
-ZipFile("ffmpeg.zip").extractall()
-print("Make ffmpeg binary executable")
-st = os.stat("ffmpeg")
-os.chmod("ffmpeg", st.st_mode | stat.S_IEXEC)
+# Definir el directorio local usando la misma ruta que el código original
+model_name = "tts_models/multilingual/multi-dataset/xtts_v2"
+local_dir = os.path.join(get_user_data_dir("tts"), model_name.replace("/", "--"))
 
-# This will trigger downloading model
-print("Downloading if not downloaded Coqui XTTS V2")
-from TTS.utils.manage import ModelManager
+# Crear el directorio si no existe
+os.makedirs(local_dir, exist_ok=True)
 
-model_name = "tts_models/multilingual/multi-dataset/xtts_v2"
-ModelManager().download_model(model_name)
-model_path = os.path.join(get_user_data_dir("tts"), model_name.replace("/", "--"))
-print("XTTS downloaded")
+# Lista de archivos necesarios
+files_to_download = ["config.json", "model.pth", "vocab.json"]
+
+# Descargar cada archivo del repositorio
+for file_name in files_to_download:
+    print(f"Downloading {file_name} from {repo_id}")
+    api.download_file(
+        repo_id=repo_id,
+        filename=file_name,
+        local_dir=local_dir,
+        repo_type="model"  # Puede ser 'model', 'dataset' o 'space'
+    )
+
+# Cargar configuración y modelo
+config_path = os.path.join(local_dir, "config.json")
+checkpoint_path = os.path.join(local_dir, "model.pth")
+vocab_path = os.path.join(local_dir, "vocab.json")
 
 config = XttsConfig()
-config.load_json(os.path.join(model_path, "config.json"))
+config.load_json(config_path)
 
 model = Xtts.init_from_config(config)
 model.load_checkpoint(
     config,
-    checkpoint_path=os.path.join(model_path, "model.pth"),
-    vocab_path=os.path.join(model_path, "vocab.json"),
+    checkpoint_path=checkpoint_path,
+    vocab_path=vocab_path,
     eval=True,
-    use_deepspeed=True,
+    use_deepspeed=False,  # Asegúrate de que no intente usar DeepSpeed
 )
-model.cuda()
+
+# No transfieras el modelo a la GPU, elimina o comenta esta línea:
+# model.cuda()
+
+print("Modelo cargado en CPU")
 
 # This is for debugging purposes only
 DEVICE_ASSERT_DETECTED = 0