Multi audio sample TTS generation w/XTTS

🟧 Using Single Voice Samples
Voice samples are stored in `/alltalk_tts/voices/` and should be named using the following format `name.wav`. These files will be listed as `name.wav` in the available voices list.

🟧 Using Multiple Voice Samples
If you have multiple voice samples for a single voice, you can organize them into subfolders within the `/alltalk_tts/voices/` directory. Each subfolder should be named according to the voice it contains, up to 5 voice samples will be randomly selected for use.

     • Each subfolder should reflect the name or type of the voice it contains (e.g., female_voice, male_voice).
     • The voice samples inside each subfolder should follow the standard .wav format.
     • An example folder path would be `/alltalk_tts/voices/mynewvoice/` and this would be listed in the available voices list as `mynewvoice/`.

This organization allows for easy selection and management of multiple voice samples while ensuring the system can correctly identify and utilize each voice. Manual CURL API requests would send the folder in the format `mynewvoice/`.

system/tts_engines/xtts/model_engine.py

@@ -37,6 +37,7 @@ try:
     import torchaudio
     import wave
     import io
+    import random
     import numpy as np
     from TTS.tts.configs.xtts_config import XttsConfig
     from TTS.tts.models.xtts import Xtts
@@ -287,7 +288,19 @@ class tts_class:
             # ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
                  
             directory = self.main_dir / "voices"
-            voices = [f for f in os.listdir(directory) if os.path.isfile(os.path.join(directory, f)) and f.endswith(".wav")]
+            # Step 1: Add .wav files in the main "voices" directory to the list
+            voices.extend([f for f in os.listdir(directory) if os.path.isfile(os.path.join(directory, f)) and f.endswith(".wav")])
+            
+            # Step 2: Walk through subfolders and add subfolder names if they contain .wav files
+            for root, dirs, files in os.walk(directory):
+                # Skip the root directory itself and only consider subfolders
+                if os.path.normpath(root) != os.path.normpath(directory):
+                    if any(f.endswith(".wav") for f in files):
+                        folder_name = os.path.basename(root) + "/"
+                        voices.append(folder_name)
+            
+            # Remove "voices/" from the list if it somehow got added
+            voices = [v for v in voices if v != "voices/"]
             
             # ↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓↓
             # ↓↓↓ Keep everything below this line ↓↓↓
@@ -470,15 +483,31 @@ class tts_class:
 
         # XTTSv2 LOCAL & Xttsv2 FT Method
         print(f"[{self.branding}Debug] Deciding if streaming or not") if self.debug_tts else None
-        print(f"[{self.branding}Debug] self.current_model_loaded", self.current_model_loaded) if self.debug_tts else None
+        print(f"[{self.branding}Debug] self.current_model_loaded is:", self.current_model_loaded) if self.debug_tts else None
         self.current_model_loaded
-        if os.path.isdir(voice):
-            wavs_files = glob.glob(os.path.join(voice, "*.wav"))
+        print(f"[{self.branding}Debug] Audio Sample Detection") if self.debug_tts else None
+        print(f"[{self.branding}Debug] Voice name sent in request is:", voice) if self.debug_tts else None
+        # Check if the voice ends with a slash, indicating it's a directory
+        if voice.endswith("/") or voice.endswith("\\"):
+            # Remove the trailing slash for proper path detection
+            voice = voice.rstrip("/\\")
+        if os.path.isdir(os.path.join(self.main_dir, "voices", voice)):
+            # Normalize the path for the directory and then search for .wav files
+            normalized_path = os.path.normpath(os.path.join(self.main_dir, "voices", voice))
+            wavs_files = glob.glob(os.path.join(normalized_path, "*.wav"))
+            print(f"[{self.branding}Debug] Directory of multiple voice samples detected. Using multiple WAV files:", wavs_files) if self.debug_tts else None            
+            # If there are more than 5 .wav files, randomly select 5
+            if len(wavs_files) > 5:
+                wavs_files = random.sample(wavs_files, 5)
+                print(f"[{self.branding}Debug] More than 5 wav files detected so only using 5x random audio samples:", wavs_files) if self.debug_tts else None
         else:
-            wavs_files = [f"{self.main_dir}/voices/{voice}"]
+            # Normalize the path for the file
+            normalized_path = os.path.normpath(os.path.join(self.main_dir, "voices", voice))
+            wavs_files = [normalized_path]
+            print(f"[{self.branding}Debug] Single voice sample detected. Using one WAV sample:", wavs_files) if self.debug_tts else None
 
         if self.current_model_loaded.startswith ("xtts"):
-            print(f"[{self.branding}Debug] Text arriving at engine {text}") if self.debug_tts else None
+            print(f"[{self.branding}Debug] Text arriving at TTS engine is: {text}") if self.debug_tts else None
             gpt_cond_latent, speaker_embedding = self.model.get_conditioning_latents(
                 audio_path=wavs_files,
                 gpt_cond_len=self.model.config.gpt_cond_len,