fixed model not loading on cpu, and fixed local

app.py

@@ -20,6 +20,7 @@ import gradio as gr
 from gradio import Progress
 import urllib.request
 import zipfile
+import socket
 #import MeCab
 #import unidic
 
@@ -28,6 +29,9 @@ nltk.download('punkt_tab')
 # Pre-download the xtts TOS agreed file
 import download_tos_agreed_file
 
+# Import the locally stored Xtts default model
+import import_locally_stored_tts_model_files
+
 # Download UniDic if it's not already installed
 #unidic.download()
 
@@ -395,6 +399,21 @@ from pydub import AudioSegment
 
 default_target_voice_path = "default_voice.wav"  # Ensure this is a valid path
 default_language_code = "en"
+
+
+# Function to check if vocab.json exists and rename it
+def rename_vocab_file_if_exists(directory):
+    vocab_path = os.path.join(directory, 'vocab.json')
+    new_vocab_path = os.path.join(directory, 'vocab.json_')
+
+    # Check if vocab.json exists
+    if os.path.exists(vocab_path):
+        # Rename the file
+        os.rename(vocab_path, new_vocab_path)
+        print(f"Renamed {vocab_path} to {new_vocab_path}")
+        return True  # Return True if the file was found and renamed
+
+
 def combine_wav_files(input_directory, output_directory, file_name):
     # Ensure that the output directory exists, create it if necessary
     os.makedirs(output_directory, exist_ok=True)
@@ -468,7 +487,7 @@ def convert_chapters_to_audio_custom_model(chapters_dir, output_audio_dir, targe
         config.load_json(custom_model['config'])
         model = Xtts.init_from_config(config)
         model.load_checkpoint(config, checkpoint_path=custom_model['model'], vocab_path=custom_model['vocab'], use_deepspeed=False)
-        model.device
+        model.to(device)
         print("Computing speaker latents...")
         gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(audio_path=[target_voice_path])
     else:
@@ -585,6 +604,11 @@ def convert_ebook_to_audio(ebook_file, target_voice_file, language, use_custom_m
         print(f"Received custom model URL: {custom_model_url}")
         download_dir = os.path.join(".", "Working_files", "custom_model")
         download_and_extract_zip(custom_model_url, download_dir)
+
+        # Check if vocab.json exists and rename it
+        if rename_vocab_file_if_exists(download_dir):
+            print("vocab.json file was found and renamed.")
+        
         custom_model = {
             'model': os.path.join(download_dir, 'model.pth'),
             'config': os.path.join(download_dir, 'config.json'),
@@ -709,5 +733,19 @@ with gr.Blocks(theme=theme) as demo:
         outputs=[download_files]
     )
 
+
+
+
 #demo.launch(share=True)
-demo.launch() # Removing share = True for Gradio Interface
+#demo.launch() # Removing share = True for Gradio Interface
+
+# Get the correct local IP or localhost
+hostname = socket.gethostname()
+local_ip = socket.gethostbyname(hostname)
+
+# Ensure Gradio runs and prints the correct local IP
+print(f"Running on local URL: http://{local_ip}:7860")
+print(f"Running on local URL: http://localhost:7860")
+
+# Your Gradio launch command
+demo.launch(server_name="0.0.0.0", server_port=7860)