feat(ocr): Add docTR OCR engine with metrics infrastructure

Add docTR as primary OCR engine with 2-tier sequential processing,
OCR metrics tracking, and simplified engine selection.

Features:
- docTR OCR engine with light+medium preprocessing tiers
- doctr_plus mode with early exit optimization (~65% fast path)
- OCR metrics dashboard with per-engine statistics
- User OCR preference persistence
- Parallel worker pool for OCR processing
- Cross-validation for extraction quality

Engine options: tesseract, doctr, doctr_plus (recommended), paddleocr

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

backend/main.py

@@ -38,12 +38,20 @@ from backend.modules.reports.routers import create_reports_router
 from backend.modules.data_entry.routers import create_data_entry_router
 from backend.modules.telegram.routers import create_telegram_router
 
-# Configure logging
+# Configure logging (level from env: DEBUG, INFO, WARNING, ERROR)
+log_level = os.getenv('LOG_LEVEL', 'INFO').upper()
 logging.basicConfig(
-    level=logging.INFO,
+    level=getattr(logging, log_level, logging.INFO),
     format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
     datefmt='%H:%M:%S'
 )
+# Reduce noise from third-party libraries
+logging.getLogger('httpcore').setLevel(logging.WARNING)
+logging.getLogger('httpx').setLevel(logging.WARNING)
+logging.getLogger('multipart').setLevel(logging.WARNING)
+logging.getLogger('doctr').setLevel(logging.WARNING)
+logging.getLogger('tensorflow').setLevel(logging.WARNING)
+logging.getLogger('PIL').setLevel(logging.WARNING)
 logger = logging.getLogger(__name__)
 
 # Global variables for background tasks