Update app.py

app.py

@@ -33,36 +33,29 @@ MODEL_NAME = "microsoft/deberta-v3-small"
 WINDOW_SIZE = 6
 WINDOW_OVERLAP = 2
 CONFIDENCE_THRESHOLD = 0.65
-BATCH_SIZE = 8  # Reduced batch size for CPU
-MAX_WORKERS = 4  # Number of worker threads for processing
+BATCH_SIZE = 8  
+MAX_WORKERS = 4 
+
 
-# IMPORTANT: Set PyTorch thread configuration at the module level
-# before any parallel work starts
 if not torch.cuda.is_available():
-    # Set thread configuration only once at the beginning
     torch.set_num_threads(MAX_WORKERS)
     try:
-        # Only set interop threads if it hasn't been set already
         torch.set_num_interop_threads(MAX_WORKERS)
     except RuntimeError as e:
         logger.warning(f"Could not set interop threads: {str(e)}")
 
-# Get password hash from environment variable (more secure)
 ADMIN_PASSWORD_HASH = os.environ.get('ADMIN_PASSWORD_HASH')
 
 if not ADMIN_PASSWORD_HASH:
     ADMIN_PASSWORD_HASH = "5e22d1ed71b273b1b2b5331f2d3e0f6cf34595236f201c6924d6bc81de27cdcb"
 
-# Excel file path for logs
 EXCEL_LOG_PATH = "/tmp/prediction_logs.xlsx"
 
-# OCR API settings
-OCR_API_KEY = "9e11346f1288957"  # Now using the complete key
+OCR_API_KEY = "9e11346f1288957"  
 OCR_API_ENDPOINT = "https://api.ocr.space/parse/image"
 OCR_MAX_PDF_PAGES = 3
 OCR_MAX_FILE_SIZE_MB = 1
 
-# Configure logging for OCR module
 ocr_logger = logging.getLogger("ocr_module")
 ocr_logger.setLevel(logging.INFO)