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