Create tts.py

tts.py

@@ -0,0 +1,52 @@
+import os
+import torch
+import torchaudio
+import spaces  # Import spaces module for Zero-GPU
+from tortoise.api import TextToSpeech
+from tortoise.utils.audio import load_audio
+
+# Create cache/output directory
+os.makedirs("outputs", exist_ok=True)
+
+# Create a global TTS model instance
+tts_model = None
+
+@spaces.GPU  # Add spaces.GPU decorator for Zero-GPU support
+async def generate_speech(text, voice_preset="random", voice_file_path=None):
+    global tts_model
+    
+    try:
+        # Initialize the model if not already initialized
+        if tts_model is None:
+            print("Initializing Tortoise-TTS model...")
+            tts_model = TextToSpeech(use_deepspeed=torch.cuda.is_available())
+            print(f"Model initialized. Using device: {next(tts_model.autoregressive.parameters()).device}")
+        
+        # Process voice sample if provided
+        voice_samples = None
+        if voice_file_path and os.path.exists(voice_file_path):
+            print(f"Loading voice from {voice_file_path}")
+            voice_samples, _ = load_audio(voice_file_path, 22050)
+            voice_samples = [voice_samples]
+            voice_preset = None
+        
+        # Generate speech
+        print(f"Generating speech for text: {text[:50]}...")
+        output_filename = f"outputs/tts_output_{hash(text) % 10000}.wav"
+        
+        gen = tts_model.tts_with_preset(
+            text,
+            voice_samples=voice_samples,
+            preset=voice_preset
+        )
+        
+        # Save the generated audio
+        torchaudio.save(output_filename, gen.squeeze(0).cpu(), 24000)
+        print(f"Speech generated and saved to {output_filename}")
+        
+        # Return the filename and audio data
+        return output_filename, (24000, gen.squeeze(0).cpu())
+        
+    except Exception as e:
+        print(f"Error generating speech: {str(e)}")
+        raise