Update app.py

app.py

@@ -379,16 +379,28 @@ def process_audio_file_optimized(file_path, task="transcribe", language="auto",
 def health_check():
     """Health check endpoint"""
     model_status = "loaded" if model_manager.pipe is not None else "not_loaded"
+    
+    # بررسی وضعیت حافظه
+    import psutil
+    memory_info = psutil.virtual_memory()
+    
     return jsonify({
         "status": "healthy",
         "model": MODEL_NAME,
         "device": str(device),
         "model_status": model_status,
         "model_timeout_minutes": MODEL_TIMEOUT_MINUTES,
+        "limits": {
+            "max_file_size_mb": FILE_LIMIT_MB,
+            "max_audio_duration_seconds": MAX_AUDIO_DURATION,
+            "chunk_length_seconds": CHUNK_LENGTH
+        },
+        "memory": {
+            "available_mb": round(memory_info.available / 1024 / 1024),
+            "used_percent": memory_info.percent
+        },
         "optimization": {
-            "fp16": torch.cuda.is_available(),
             "batch_size": BATCH_SIZE,
-            "chunk_length": CHUNK_LENGTH,
             "max_workers": MAX_WORKERS
         },
         "supported_languages": list(SUPPORTED_LANGUAGES.keys())
@@ -673,8 +685,24 @@ def cleanup_model_on_shutdown(exception):
     model_manager.cleanup_model()
 
 if __name__ == '__main__':
+    # نصب psutil در صورت عدم وجود
     try:
+        import psutil
+    except ImportError:
+        logger.warning("psutil not installed. Memory monitoring disabled.")
+        
+    try:
+        # تنظیمات Flask برای فایل‌های بزرگ
+        app.config['MAX_CONTENT_LENGTH'] = MAX_FILE_SIZE
+        app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 0
+        
+        logger.info(f"Starting server with max file size: {FILE_LIMIT_MB}MB")
+        logger.info(f"Max audio duration: {MAX_AUDIO_DURATION/60:.1f} minutes")
+        
         app.run(host='0.0.0.0', port=7860, debug=False, threaded=True)
+    except KeyboardInterrupt:
+        logger.info("Server shutdown requested")
     finally:
         # پاکسازی نهایی
+        logger.info("Cleaning up resources...")
         model_manager.cleanup_model()