Update app.py

app.py

@@ -25,21 +25,6 @@ if is_restricted_environment():
 else:
     print("🔧 Local environment detected - Unsloth optimizations enabled")
 
-# Check if we're in ZeroGPU or similar restricted environment
-def is_restricted_environment():
-    return (
-        os.getenv("ZERO_GPU") or 
-        "zero" in str(os.getenv("SPACE_ID", "")).lower() or
-        os.getenv("SPACES_ZERO_GPU")
-    )
-
-# Disable Unsloth optimizations in restricted environments
-if is_restricted_environment():
-    os.environ["UNSLOTH_DISABLE"] = "1"
-    os.environ["DISABLE_UNSLOTH"] = "1"
-    os.environ["UNSLOTH_IGNORE_ERRORS"] = "1"
-    print("🚀 ZeroGPU detected - Unsloth optimizations disabled for compatibility")
-
 import torch
 import gradio as gr
 import numpy as np
@@ -94,7 +79,7 @@ def get_speakers_dict():
 
 @spaces.GPU()
 def initialize_model_once():
-    """Initialize model exactly like your old working version"""
+    """Initialize model with retry logic for Unsloth failures"""
     global _tts_model, _speakers_dict, _model_initialized, _initialization_in_progress
     
     if _model_initialized:
@@ -110,31 +95,40 @@ def initialize_model_once():
     
     _initialization_in_progress = True
     
+    max_retries = 2
+    retry_delay = 5  # seconds
+    
     try:
         logger.info("Initializing Bambara TTS model...")
         start_time = time.time()
         
-        # Use the correct import path
         from maliba_ai.tts.inference import BambaraTTSInference
         
-        model = BambaraTTSInference()
-        speakers = get_speakers_dict()
-        
-        if not speakers:
-            raise ValueError("Failed to load speakers dictionary")
-        
-        _tts_model = model
-        _speakers_dict = speakers
-        _model_initialized = True
-        
-        elapsed = time.time() - start_time
-        logger.info(f"Model initialized successfully in {elapsed:.2f} seconds!")
-        
-        return _tts_model, _speakers_dict
-        
+        for attempt in range(max_retries):
+            try:
+                model = BambaraTTSInference()
+                speakers = get_speakers_dict()
+                
+                if not speakers:
+                    raise ValueError("Failed to load speakers dictionary")
+                
+                _tts_model = model
+                _speakers_dict = speakers
+                _model_initialized = True
+                
+                elapsed = time.time() - start_time
+                logger.info(f"Model initialized successfully in {elapsed:.2f} seconds!")
+                return _tts_model, _speakers_dict
+                
+            except Exception as e:
+                if "unsloth_compiled_module_qwen2" in str(e) and attempt < max_retries - 1:
+                    logger.warning(f"Unsloth compilation failed, retrying in {retry_delay} seconds... (attempt {attempt + 1}/{max_retries})")
+                    time.sleep(retry_delay)
+                else:
+                    raise e
+                    
     except Exception as e:
-        logger.error(f"Failed to initialize model: {e}")
-        _initialization_in_progress = False
+        logger.error(f"Failed to initialize model after {max_retries} attempts: {e}")
         raise e
     finally:
         _initialization_in_progress = False
@@ -406,7 +400,7 @@ def build_interface():
             - **📱 Usage**: Educational, accessibility, and cultural preservation
             
             ### 🎭 Available Speakers:
-            {', '.join(SPEAKER_NAMES)}
+            {ettes.join(SPEAKER_NAMES)}
             
             **License**: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)