Update app.py

app.py

@@ -1,10 +1,22 @@
+import os
+
+# Set environment variables to disable compilation and optimize PyTorch
+os.environ["TORCHDYNAMO_DISABLE"] = "1"
+os.environ["TORCH_COMPILE_DISABLE"] = "1"
+os.environ["PYTORCH_DISABLE_CUDNN_BENCHMARK"] = "1"
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+import torch
 import gradio as gr
 import numpy as np
-import os
 import spaces
 import logging
 from huggingface_hub import login
 
+# Disable PyTorch compilation completely
+torch._dynamo.config.disable = True
+torch._dynamo.config.suppress_errors = True
+
 # Set up logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -141,7 +153,6 @@ def build_interface():
         
         with gr.Row():
             with gr.Column(scale=2):
-                # Input section
                 text_input = gr.Textbox(
                     label="📝 Bambara Text",
                     placeholder="Type your Bambara text here...",
@@ -229,23 +240,14 @@ def build_interface():
                     outputs=[text_input, speaker_dropdown, use_advanced, temperature, top_k, top_p, max_tokens]
                 )
         
-        # Information section
         with gr.Accordion("ℹ️ About", open=False):
             gr.Markdown("""
             **⚠️ This is an experimental Bambara TTS model.**
             
             - **Model**: Based on SparkTTS architecture with BiCodec
-            - **Languages**: Bambara (bm)
+            - **Languages**: Bambara (bm)  
             - **Speakers**: 5 different voice options
             - **Sample Rate**: 16kHz
-            - **Architecture**: Neural codec with semantic and global tokens
-            
-            ## 🚀 How to Use
-            
-            1. **Enter Text**: Type your Bambara text in the input box
-            2. **Choose Speaker**: Select from 5 available voice options
-            3. **Advanced Settings**: Optionally adjust generation parameters
-            4. **Generate**: Click the generate button to create speech
             """)
         
         def toggle_advanced(use_adv):