Update app.py

app.py

@@ -1,31 +1,30 @@
 import gradio as gr
 import torch
-from your_model_module import YourTTSModel, YourTTSProcessor  # Replace with your actual imports
+from coqui_tts import TTS
+from coqui_tts.utils import audio
 
-# Load the model and processor
-model = YourTTSModel.from_pretrained("config.json")
-model.load_state_dict(torch.load("best_model.pth"))
-model.eval()  # Set the model to evaluation mode
+# Load the Coqui TTS model and configuration
+model_path = "best_model.pth"  # Directory where the model is saved
+config_path = "config.json"
 
-processor = YourTTSProcessor.from_pretrained("config.json")
+# Initialize TTS with your model and configuration
+tts = TTS(model_path=model_path, config_path=config_path)
 
 def generate_speech(text):
-    # Process the input text
-    inputs = processor(text, return_tensors="pt")
-    
     # Generate speech using the model
-    with torch.no_grad():  # No need to compute gradients
-        outputs = model.generate(**inputs)
-    
-    # Process the output to an audio format
-    audio = outputs.squeeze().numpy()  # Adjust this based on how your model outputs data
-    return audio
+    audio_path = tts.tts_to_file(text, "output.wav")
+
+    # Load the generated audio file
+    with open(audio_path, "rb") as f:
+        audio_data = f.read()
+
+    return audio_data
 
 # Define the Gradio interface
 iface = gr.Interface(
     fn=generate_speech,
     inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
-    outputs=gr.Audio(type="numpy"),
+    outputs=gr.Audio(type="file"),
     title="Text-to-Speech with Coqui TTS",
     description="Generate speech from text using a custom Coqui TTS model."
 )