OCR Data Extraction Validation System: - Add 7 validation rules (amount range, TVA ratio, payment sum, etc.) - Add Medium preprocessing to replace Heavy (fixes digit concatenation) - Add validation warnings to API responses - Flag receipts needing manual review (needs_manual_review field) - Add database migration for needs_manual_review column CLIENT CUI Extraction Improvements: - Support all format variations: CIF CLIENT:, CLIENT C.U.I/C.I.F., etc. - Handle OCR errors (R0 vs RO, C1F vs CIF) - Add client_name, client_cui, client_address to API response - Add validation fields to API response (was missing) QA Review: 12 issues found, 9 fixed (5 errors + 4 warnings) - Fixed type safety in validation rules - Fixed ZeroDivisionError risk - Fixed schema mismatch (Optional[bool] for needs_manual_review) - All 37 unit tests passing 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
15 KiB
Implementation Plan: bon-ocr-validation
Status: ✅ COMPLETE Completed: 2025-12-30T19:15:00Z
Feature: OCR Data Extraction Validation System Priority: Critical (P0 - Production Bug) Estimated Effort: 2-3 days Created: 2025-12-30T17:25:00Z
Progress Tracker
| Task | Status | Completed |
|---|---|---|
| Task 1: Create validation module structure | ✅ Done | 2025-12-30 17:30 |
| Task 2: Implement validation rules (7 rules) | ✅ Done | 2025-12-30 17:35 |
| Task 3: Create validation engine orchestrator | ✅ Done | 2025-12-30 18:05 |
| Task 4: Write unit tests for validation | ✅ Done | 2025-12-30 18:15 |
| Task 5: Add Medium OCR preprocessing | ✅ Done | 2025-12-30 18:25 |
| Task 6: Update ExtractionResult schema | ✅ Done | 2025-12-30 18:35 |
| Task 7: Refactor merge_extractions with validation | ✅ Done | 2025-12-30 18:50 |
| Task 8: Update API schemas | ✅ Done | 2025-12-30 18:55 |
| Task 9: Create database migration | ✅ Done | 2025-12-30 19:05 |
| Task 10: Write integration tests | ✅ Done | 2025-12-30 19:10 |
| Task 11: Test with Five-Holding receipt | ✅ Done | 2025-12-30 19:15 |
Tasks
Task 1: Create validation module structure
- Status: ✅ Done (2025-12-30 17:30)
- Phase: Day 1 - Core Validation
- Files:
backend/modules/data_entry/services/ocr/validation.py(NEW) - Lines: ~50 lines
- Description:
- Create
backend/modules/data_entry/services/ocr/directory - Create
validation.pywith base classes - Define
ValidationRuleabstract base class withvalidate()method - Define
ValidationResultdataclass (is_valid, confidence_penalty, message) - Add module docstring and imports
- Create
- Dependencies: None
- Success Criteria: Module loads without errors, base classes defined
Task 2: Implement validation rules (7 rules)
-
Status: ✅ Done (2025-12-30 17:35)
-
Phase: Day 1 - Core Validation
-
Files:
backend/modules/data_entry/services/ocr/validation.py -
Lines: ~300 lines added
-
Description: Implement 7 concrete validation rule classes:
- AmountRangeRule - Check 0.01 ≤ amount ≤ 100,000 RON
- TVARatioRule - Check TVA is 5-24% of TOTAL
- PaymentSumRule - Check CARD + NUMERAR = TOTAL (±0.02 tolerance)
- TVAEntriesSumRule - Check Σ(TVA entries) = TVA TOTAL (±0.02)
- CUIFormatRule - Check RO + 6-10 digits format
- CUIChecksumRule - Romanian CIF Mod 11 checksum algorithm
- InterOCRConsistencyRule - Flag if values differ >10x ratio
Each rule should:
- Inherit from
ValidationRule - Implement
validate(data: dict) -> ValidationResult - Have clear docstrings with examples
- Return confidence penalty (0.0-1.0) when validation fails
-
Dependencies: Task 1
-
Success Criteria: All 7 rules implemented, can instantiate and call validate()
Task 3: Create validation engine orchestrator
-
Status: ✅ Done (2025-12-30 18:05)
-
Phase: Day 1 - Core Validation
-
Files:
backend/modules/data_entry/services/ocr/validation.py -
Lines: ~50 lines added
-
Description:
- Create
OCRValidationEngineclass - Method:
validate_extraction(extraction_result, light_result, heavy_result) - Apply all rules in order (sanity → cross-field → inter-OCR)
- Aggregate results: collect all warnings, calculate overall penalty
- Return enhanced extraction result with:
needs_manual_review: bool(if any rule fails critically)validation_warnings: list[str]confidence_adjustments: dict[str, float]
- Add helper method:
normalize_cui(cui: str) -> str(add RO prefix)
- Create
-
Dependencies: Task 2
-
Success Criteria: Engine can validate extraction, returns enhanced result
Task 4: Write unit tests for validation
-
Status: ✅ Done (2025-12-30 18:15)
-
Phase: Day 1 - Core Validation
-
Files:
backend/modules/data_entry/tests/test_ocr_validation.py(NEW) -
Lines: ~300 lines
-
Description: Write comprehensive unit tests (>90% coverage):
AmountRangeRule (4 tests):
- test_amount_within_range_passes
- test_amount_too_high_fails
- test_amount_too_low_fails
- test_none_amount_passes
TVARatioRule (3 tests):
- test_valid_tva_ratio_passes (19%)
- test_tva_too_high_fails (>24%)
- test_tva_too_low_fails (<5%)
PaymentSumRule (4 tests):
- test_payment_sum_matches_total_passes
- test_payment_sum_mismatch_fails
- test_tolerance_within_002_passes
- test_missing_payment_methods_passes
TVAEntriesSumRule (3 tests):
- test_tva_entries_sum_matches
- test_tva_entries_mismatch_fails
- test_tolerance_within_002_passes
CUIChecksumRule (5 tests):
- test_valid_cui_checksum_passes (RO10562600)
- test_invalid_cui_checksum_fails
- test_cui_without_ro_prefix_normalized
- test_cui_with_r0_prefix_normalized
- test_non_numeric_cui_fails
InterOCRConsistencyRule (3 tests):
- test_values_within_10x_passes
- test_values_over_10x_fails
- test_one_value_missing_passes
OCRValidationEngine (5 tests):
- test_engine_applies_all_rules
- test_engine_aggregates_warnings
- test_engine_sets_manual_review_flag
- test_engine_calculates_confidence_penalties
- test_normalize_cui_helper
-
Dependencies: Task 3
-
Success Criteria: All tests pass, pytest coverage >90%
Task 5: Add Medium OCR preprocessing
-
Status: ✅ Done (2025-12-30 18:25)
-
Phase: Day 2 - OCR Integration
-
Files:
backend/modules/data_entry/services/image_preprocessor.py -
Lines: ~80 lines added
-
Description:
- Add
preprocess_medium(image: Image.Image) -> Image.Imagemethod - Apply moderate enhancements:
- Grayscale conversion
- Contrast enhancement (factor=1.5, not 2.0)
- Gentle sharpening (factor=1.3)
- Light noise reduction (MedianFilter size=3)
- Do NOT apply:
- Aggressive binarization (causes digit concatenation)
- Morphological operations (erosion/dilation)
- Heavy contrast (factor=2.0)
- Add docstring explaining difference from Heavy preprocessing
- Mark
preprocess_heavy()as deprecated with comment
- Add
-
Dependencies: None (parallel with Task 1-4)
-
Success Criteria: Method returns preprocessed image, no extreme distortion
Task 6: Update ExtractionResult schema
-
Status: ✅ Done (2025-12-30 18:35)
-
Phase: Day 2 - OCR Integration
-
Files:
backend/modules/data_entry/services/ocr_extractor.pybackend/modules/data_entry/schemas/ocr.py
-
Lines: ~50 lines modified, ~30 added
-
Description:
In ocr_extractor.py:
- Add fields to
ExtractionResultdataclass (after existing fields):# Validation tracking needs_manual_review: bool = False validation_warnings: list[str] = field(default_factory=list) validation_errors: list[str] = field(default_factory=list) confidence_adjustments: dict[str, float] = field(default_factory=dict) - Update
to_dict()method to include new fields - Fix CLIENT CUI patterns (more flexible for OCR variations):
- Make colon optional:
:?\s* - Make RO prefix optional:
(?:R[O0])?\s* - Pattern:
r'CLIENT\s+C\.\s*U\.\s*I\.?\s*/\s*C\.\s*[I1]\.\s*F\.?\s*:?\s*(?:R[O0])?\s*(\d{6,10})'
- Make colon optional:
In schemas/ocr.py:
- Add
ValidationWarningschema:class ValidationWarning(BaseModel): field: str severity: str # "warning" | "error" message: str - Add to
ExtractionDataschema (line ~57):needs_manual_review: bool = False validation_warnings: list[ValidationWarning] = []
- Add fields to
-
Dependencies: Task 3 (needs ValidationResult structure)
-
Success Criteria: Schemas load, can serialize/deserialize with new fields
Task 7: Refactor merge_extractions with validation
-
Status: ✅ Done (2025-12-30 18:50)
-
Phase: Day 2 - OCR Integration
-
Files:
backend/modules/data_entry/services/ocr_service.py -
Lines: ~200 lines modified
-
Description:
Replace Step 2 Heavy OCR with Medium OCR (line ~130):
- Change
self._preprocess_heavy(image)toself._preprocess_medium(image) - Update logging: "Step 2: PaddleOCR + Medium preprocessing"
- Update variable names:
result_heavy→result_medium,conf_heavy→conf_medium
Refactor
_merge_extractions()method (lines 240-386):- Import validation engine:
from .ocr.validation import OCRValidationEngine - Instantiate engine:
validator = OCRValidationEngine() - For each field (AMOUNT, TVA, CUI, DATE):
- Get both Light and Medium values
- Run validation on both values
- Apply confidence penalties from validation results
- Choose value with ADJUSTED confidence (not raw)
- Log decision with validation notes
- After merge, run cross-field validations:
- Payment sum validation (CARD + CASH = TOTAL)
- TVA entries sum validation
- If mismatch and confidence < 80%, auto-correct TOTAL from payment sum
- Call validator engine:
result = validator.validate_extraction(result, light_result, medium_result) - Return enhanced result with validation warnings
Add structured logging:
- Log each merge decision with confidence scores
- Log validation failures with field names
- Log auto-corrections with old/new values
- Change
-
Dependencies: Task 3, Task 5, Task 6
-
Success Criteria: Merge logic uses validation, auto-correction works
Task 8: Update API schemas and router
-
Status: ✅ Done (2025-12-30 18:55)
-
Phase: Day 2 - OCR Integration
-
Files:
backend/modules/data_entry/routers/ocr.py -
Lines: ~40 lines modified
-
Description:
- Update
OCRResponseschema to include validation fields:needs_manual_review: bool = False validation_warnings: list[ValidationWarning] = [] confidence_info: dict[str, float] = {} # field -> adjusted confidence - In
/process-receiptendpoint (line ~106):- Pass validation warnings from OCR result to response
- Add log message if needs_manual_review=True
- Return HTTP 200 with warnings (don't block)
- Update endpoint docstring to mention validation behavior
- Update
-
Dependencies: Task 6, Task 7
-
Success Criteria: API returns validation warnings, save not blocked
Task 9: Create database migration
-
Status: ✅ Done (2025-12-30 19:05)
-
Phase: Day 2 - OCR Integration
-
Files:
backend/modules/data_entry/migrations/versions/XXX_add_needs_manual_review.py(NEW) -
Lines: ~30 lines
-
Description:
- Generate Alembic migration:
alembic revision -m "add needs_manual_review to receipts" - Add column to
receiptstable:op.add_column('receipts', sa.Column('needs_manual_review', sa.Boolean(), nullable=True, default=False) ) - Add downgrade to remove column
- Test migration:
alembic upgrade headthenalembic downgrade -1
- Generate Alembic migration:
-
Dependencies: None (parallel)
-
Success Criteria: Migration runs without errors, column added
Task 10: Write integration tests
-
Status: ✅ Done (2025-12-30 19:10)
-
Phase: Day 3 - Testing & Polish
-
Files:
backend/modules/data_entry/tests/test_ocr_validation_integration.py(NEW) -
Lines: ~200 lines
-
Description: Write integration tests with real OCR service:
Test 1: Five-Holding production case
- Load
docs/data-entry/igiena 14 decembrie five-holding.pdf - Run full OCR pipeline
- Assert: TOTAL = 85.99 (NOT 859,762.16)
- Assert: TVA = 14.92 (NOT 149,214.92)
- Assert: No magnitude errors >10x
Test 2: Payment sum validation
- Mock OCR results: TOTAL=100.00, CARD=50.00, CASH=40.00
- Assert: needs_manual_review=True
- Assert: "Payment sum mismatch" in warnings
Test 3: Payment sum auto-correction
- Mock: TOTAL=859762.16 (confidence=0.75), CARD=85.99, CASH=0.00
- Assert: TOTAL auto-corrected to 85.99
- Assert: "Auto-corrected from payment sum" in warnings
Test 4: TVA entries sum validation
- Mock: TVA_TOTAL=14.92, TVA_A=12.00, TVA_B=2.00
- Assert: needs_manual_review=True (sum=14.00 ≠ 14.92)
Test 5: CUI checksum validation
- Mock: CUI="RO10562600" (valid checksum)
- Assert: passes validation
- Mock: CUI="RO12345678" (invalid checksum)
- Assert: confidence penalty applied
Test 6: Inter-OCR consistency
- Mock: Light=85.99, Medium=859762.16
- Assert: Light value chosen (ratio >10x)
- Assert: "Inter-OCR inconsistency" in warnings
Test 7: All validations pass (clean receipt)
- Mock high-quality receipt with correct values
- Assert: needs_manual_review=False
- Assert: validation_warnings empty
Test 8: Medium OCR doesn't cause errors
- Load clear PDF receipt
- Assert: Medium OCR values within 10x of Light
- Assert: No digit concatenation errors
- Load
-
Dependencies: Task 7, Task 8
-
Success Criteria: All 8 integration tests pass
Task 11: Test with Five-Holding receipt (Manual)
-
Status: ✅ Done (2025-12-30 19:15)
-
Phase: Day 3 - Testing & Polish
-
Files: Manual testing checklist
-
Description: Manual end-to-end testing with production receipt:
-
Start backend services:
- SSH tunnel:
./ssh-tunnel-prod.sh start - Backend:
./start-backend.sh
- SSH tunnel:
-
Upload Five-Holding receipt:
- File:
docs/data-entry/igiena 14 decembrie five-holding.pdf - Use
/api/ocr/process-receiptendpoint
- File:
-
Verify extracted values:
- ✅ TOTAL: 85.99 LEI (NOT 859,762.16)
- ✅ TVA: 14.92 LEI (NOT 149,214.92)
- ✅ CUI: R010562600
- ✅ Date: 2024-12-14
- ✅ CARD: 85.99 LEI
-
Verify validation:
- ✅ needs_manual_review = False (values are correct)
- ✅ validation_warnings empty (or only informational)
- ✅ Payment sum matches (CARD = TOTAL)
- ✅ TVA ratio valid (14.92/85.99 = 17.35%)
-
Test other receipts (regression):
- Upload 3-5 other receipts from
docs/data-entry/ - Verify no new false positives
- Verify existing correct extractions still work
- Upload 3-5 other receipts from
-
Test error cases:
- Upload receipt with wrong OCR (synthetic test)
- Verify warnings displayed
- Verify save button works (not blocked)
-
-
Dependencies: Task 10
-
Success Criteria: All manual tests pass, production bug fixed
Implementation Timeline
Day 1: Core Validation (Tasks 1-4)
- Morning: Tasks 1-2 (validation module + rules)
- Afternoon: Tasks 3-4 (engine + unit tests)
- Checkpoint: All unit tests pass (>90% coverage)
Day 2: OCR Integration (Tasks 5-9)
- Morning: Tasks 5-6 (Medium OCR + schemas)
- Afternoon: Tasks 7-9 (merge refactor + API + migration)
- Checkpoint: Five-Holding receipt extracts correct values
Day 3: Testing & Polish (Tasks 10-11)
- Morning: Task 10 (integration tests)
- Afternoon: Task 11 (manual testing + bug fixes)
- Checkpoint: Production-ready, all tests pass
Success Metrics
- ✅ All 20+ unit tests pass
- ✅ All 8 integration tests pass
- ✅ Five-Holding receipt: 85.99 not 859,762.16
- ✅ pytest coverage >90%
- ✅ No regressions on existing receipts
- ✅ Manual testing checklist complete
Rollback Plan
If issues arise:
- Revert migration:
alembic downgrade -1 - Revert code changes:
git revert {commit} - Fallback to Light + Tesseract only (skip Medium)
- Add feature flag:
OCR_VALIDATION_ENABLED=false
Plan Created: 2025-12-30T17:25:00Z Ready for Implementation: Yes