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>

shared/auth/middleware.py

@@ -246,7 +246,6 @@ class AuthenticationMiddleware(BaseHTTPMiddleware):
         Returns:
             Response-ul HTTP
         """
-        print(f"[ORIGINAL MIDDLEWARE] dispatch called for path: {request.url.path}")
         start_time = time.time()
         path = request.url.path
 
@@ -268,9 +267,7 @@ class AuthenticationMiddleware(BaseHTTPMiddleware):
             return response
         
         # Extrage token-ul
-        print(f"[MIDDLEWARE DEBUG] Extracting token for path: {path}")
         token = self._extract_token_from_header(request)
-        print(f"[MIDDLEWARE DEBUG] Extracted token: {token[:30] if token else 'None'}...")
         
         if not token:
             # Nu există token - pentru endpoint-urile protejate returnează 401
@@ -289,9 +286,7 @@ class AuthenticationMiddleware(BaseHTTPMiddleware):
             )
         
         # Validează token-ul
-        print(f"[MIDDLEWARE DEBUG] Validating token: {token[:30]}...")
         token_data = jwt_handler.verify_token(token)
-        print(f"[MIDDLEWARE DEBUG] Token validation result: {token_data}")
         
         if not token_data:
             # Token invalid