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>

tests/ocr-validation/test_receipts_parallel.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python3
+"""Test receipts in PARALLEL to measure real worker benefit."""
+
+import json
+import os
+import time
+import requests
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from datetime import datetime, timedelta
+from jose import jwt
+
+API_BASE = "http://localhost:8000"
+PDF_FOLDER = "/mnt/e/proiecte/ab-worktrees/doctr-ocr-metrics/docs/data-entry"
+EXPECTED_FILE = "/mnt/e/proiecte/ab-worktrees/doctr-ocr-metrics/tests/ocr-validation/expected_receipts.json"
+
+def get_jwt_token():
+    secret_key = os.getenv('JWT_SECRET_KEY', 'generate_with_secrets_token_urlsafe_32')
+    now = datetime.utcnow()
+    payload = {
+        "username": "MARIUS", "user_id": 1, "companies": ["604"],
+        "permissions": ["read", "write"], "exp": now + timedelta(hours=1),
+        "iat": now, "type": "access"
+    }
+    return jwt.encode(payload, secret_key, algorithm="HS256")
+
+def submit_job(pdf_path, headers):
+    """Submit OCR job and return job_id immediately."""
+    filename = os.path.basename(pdf_path)
+    try:
+        with open(pdf_path, "rb") as f:
+            files = {"file": (filename, f, "application/pdf")}
+            response = requests.post(
+                f"{API_BASE}/api/data-entry/ocr/extract?engine=doctr_plus",
+                files=files, headers=headers, timeout=30
+            )
+        if response.status_code == 200:
+            return response.json().get("job_id"), filename, None
+        return None, filename, f"HTTP {response.status_code}"
+    except Exception as e:
+        return None, filename, str(e)
+
+def wait_for_job(job_id, filename, headers, timeout=180):
+    """Wait for job completion."""
+    start = time.time()
+    while time.time() - start < timeout:
+        try:
+            resp = requests.get(
+                f"{API_BASE}/api/data-entry/ocr/jobs/{job_id}/wait?timeout=30",
+                headers=headers, timeout=35
+            )
+            if resp.status_code == 200:
+                data = resp.json()
+                status = data.get("status")
+                if status == "completed":
+                    result = data.get("result", {})
+                    conf = result.get("overall_confidence", 0)
+                    return {"success": True, "conf": conf, "time": time.time() - start}
+                elif status == "error":
+                    return {"success": False, "error": data.get("error", "unknown"), "time": time.time() - start}
+            time.sleep(1)
+        except Exception as e:
+            time.sleep(1)
+    return {"success": False, "error": "timeout", "time": time.time() - start}
+
+def main():
+    # Load receipts
+    with open(EXPECTED_FILE) as f:
+        data = json.load(f)
+    receipts = data.get("receipts", data)
+    receipts = [r for r in receipts if r.get("pages", 1) == 1]
+    
+    token = get_jwt_token()
+    headers = {"Authorization": f"Bearer {token}"}
+    
+    print(f"\n{'='*60}")
+    print(f"PARALLEL TEST: {len(receipts)} receipts")
+    print(f"{'='*60}\n")
+    
+    # PHASE 1: Submit ALL jobs rapidly
+    print("Phase 1: Submitting all jobs...")
+    total_start = time.time()
+    jobs = []
+    
+    for r in receipts:
+        pdf_path = os.path.join(PDF_FOLDER, r["filename"])
+        if os.path.exists(pdf_path):
+            job_id, filename, error = submit_job(pdf_path, headers)
+            if job_id:
+                jobs.append((job_id, filename))
+            else:
+                print(f"  Submit failed: {filename} - {error}")
+    
+    submit_time = time.time() - total_start
+    print(f"Submitted {len(jobs)} jobs in {submit_time:.1f}s")
+    
+    # PHASE 2: Wait for ALL results in parallel
+    print("\nPhase 2: Waiting for results...")
+    wait_start = time.time()
+    results = []
+    
+    with ThreadPoolExecutor(max_workers=26) as executor:
+        futures = {executor.submit(wait_for_job, job_id, fn, headers): fn 
+                   for job_id, fn in jobs}
+        
+        for future in as_completed(futures):
+            filename = futures[future]
+            result = future.result()
+            result["filename"] = filename
+            results.append(result)
+            
+            if result["success"]:
+                print(f"  OK: {filename[:45]:47} {result['time']:5.1f}s  conf={result['conf']:.0%}")
+            else:
+                print(f"  ERR: {filename[:45]:47} {result['time']:5.1f}s  {result.get('error','?')}")
+    
+    total_time = time.time() - total_start
+    
+    # Summary
+    print(f"\n{'='*60}")
+    print("SUMMARY")
+    print(f"{'='*60}")
+    successful = [r for r in results if r["success"]]
+    failed = [r for r in results if not r["success"]]
+    
+    print(f"Success: {len(successful)}/{len(results)}")
+    print(f"Submit phase:  {submit_time:.1f}s")
+    print(f"Wait phase:    {time.time() - wait_start:.1f}s")
+    print(f"TOTAL TIME:    {total_time:.1f}s")
+    
+    if successful:
+        times = [r["time"] for r in successful]
+        print(f"\nPer-job: avg={sum(times)/len(times):.1f}s, min={min(times):.1f}s, max={max(times):.1f}s")
+
+if __name__ == "__main__":
+    main()