diff --git a/.auto-build/memory/gotchas.json b/.auto-build/memory/gotchas.json deleted file mode 100644 index e69de29..0000000 diff --git a/.auto-build/memory/patterns.json b/.auto-build/memory/patterns.json deleted file mode 100644 index e69de29..0000000 diff --git a/.auto-build/specs/bon-ocr-validation/SUMMARY.md b/.auto-build/specs/bon-ocr-validation/SUMMARY.md deleted file mode 100644 index 9f95c5f..0000000 --- a/.auto-build/specs/bon-ocr-validation/SUMMARY.md +++ /dev/null @@ -1,207 +0,0 @@ -# OCR Data Extraction Validation System - Summary - -**Spec Location:** `/mnt/e/proiecte/roa2web/.auto-build/specs/bon-ocr-validation/spec.md` -**Created:** 2025-12-30 -**Complexity:** High (2-3 days) -**Priority:** Critical (P0 - Production Bug) - ---- - -## Problem - -Production OCR extracts wrong values due to Heavy preprocessing causing digit concatenation on clear PDFs: -- **Light OCR (98%):** 85.99 LEI ✅ -- **Heavy OCR (88%):** 859,762.16 LEI ❌ (10,000x error!) -- **Final Result:** 859,762.16 LEI ❌ (wrong source chosen) - ---- - -## Solution - -### 4-Layer Validation System - -1. **Absolute Sanity Checks** - - Amount: 0.01 - 100,000 RON - - Date: not future, not older than 10 years - - CUI: 6-10 digits + Mod 11 checksum - -2. **Cross-Field Validation** - - TVA: 5-24% of TOTAL - - CARD + NUMERAR = TOTAL (±0.02) - - Σ(TVA entries) = TVA TOTAL (±0.02) - -3. **Inter-OCR Consistency** - - Flag if values differ >10x - - Prefer validation-passing values - -4. **Auto-Correction** - - Use payment sum if TOTAL wrong - - Recalculate TOTAL from TVA if needed - -### Replace Heavy with Medium OCR - -- **Remove:** Heavy preprocessing (causes digit concatenation) -- **Add:** Medium preprocessing (moderate enhancements, no binarization) -- **Keep:** Light (step 1), Tesseract (step 3) - -### Enhanced CUI Extraction - -- Romanian CIF Mod 11 checksum validation -- OCR-tolerant patterns (spaces, C1F errors) -- Format normalization (always add RO prefix) - ---- - -## Key Requirements - -✅ **Non-blocking warnings** - Allow save with warnings -✅ **Manual review flag** - `needs_manual_review=TRUE` when confidence < 85% -✅ **Cross-validation** - Payment sum & TVA sum checks -✅ **Apply to new uploads only** - No reprocessing - ---- - -## Critical Files (10 total) - -### Files to CREATE (3) - -1. **`backend/modules/data_entry/services/ocr/validation.py`** (~400 lines) - - `ValidationRule` base class - - `AmountRangeRule`, `TVARatioRule`, `PaymentSumRule`, `CUIChecksumRule` - - `OCRValidationEngine` orchestrator - -2. **`backend/modules/data_entry/tests/test_ocr_validation.py`** (~300 lines) - - Unit tests for validation rules (>90% coverage) - - 20+ test cases - -3. **`backend/modules/data_entry/tests/test_ocr_validation_integration.py`** (~200 lines) - - Integration tests with real receipts - - Five-Holding production case test - -### Files to MODIFY (6) - -1. **`backend/modules/data_entry/services/ocr_service.py`** (~200 lines modified) - - Replace `_merge_extractions()` with validation-aware logic - - Replace Heavy with Medium OCR (line ~130) - - Add validation engine call (line ~204) - -2. **`backend/modules/data_entry/services/ocr_extractor.py`** (~80 lines modified) - - Add validation fields to `ExtractionResult` dataclass - - Fix CLIENT CUI patterns (OCR-tolerant) - - Add CUI normalization & Mod 11 checksum validation - -3. **`backend/modules/data_entry/services/image_preprocessor.py`** (~80 lines added) - - Add `preprocess_medium()` method - - Mark `preprocess_heavy()` as deprecated - -4. **`backend/modules/data_entry/routers/ocr.py`** (~40 lines modified) - - Update response with validation warnings - - Add `needs_manual_review` flag - -5. **`backend/modules/data_entry/schemas/ocr.py`** (~20 lines added) - - Add `ValidationWarning` schema - - Add validation fields to `ExtractionData` - -6. **`backend/modules/data_entry/migrations/versions/XXX_add_needs_manual_review.py`** (~30 lines) - - Add `needs_manual_review` column (nullable BOOLEAN) - -### Frontend Files (2 - optional for Phase 1) - -1. **`src/modules/data-entry/views/receipts/ReceiptCreateView.vue`** - - Display validation warnings section - - Show manual review badge - -2. **`src/modules/data-entry/components/ocr/OCRPreview.vue`** - - Show inter-OCR consistency warning - ---- - -## Acceptance Criteria - -### Critical (Must Pass) - -✅ **AC-1:** Five-Holding receipt extracts 85.99 (NOT 859,762.16) -✅ **AC-2:** Save button works with warnings (not blocked) -✅ **AC-3:** CARD + NUMERAR = TOTAL validation -✅ **AC-4:** Σ(TVA entries) = TVA TOTAL validation -✅ **AC-5:** CUI Mod 11 checksum validation - -### Test Coverage - -- **Unit tests:** 20+ test cases, >90% coverage -- **Integration tests:** 10+ real receipt tests -- **Manual testing:** 6 scenarios (Five-Holding, faded receipt, payment methods, etc.) - ---- - -## Implementation Priority - -### Day 1: Core Validation -1. Create `ocr/validation.py` module -2. Implement 7 validation rules -3. Write unit tests -4. ✅ Checkpoint: All unit tests pass - -### Day 2: OCR Integration -1. Add `preprocess_medium()` method -2. Update `_merge_extractions()` with validation -3. Update API schemas -4. Add database migration -5. ✅ Checkpoint: Five-Holding receipt works - -### Day 3: Testing & Polish -1. Write integration tests -2. Update frontend components -3. Manual testing -4. Bug fixes -5. ✅ Checkpoint: Production-ready - ---- - -## Risks & Mitigations - -| Risk | Mitigation | -|------|------------| -| Medium OCR still causes errors | Tesseract fallback + validation catches issues | -| CUI validation too strict | Warning only (not error), allow override | -| Performance impact | Validation <10ms (negligible vs. OCR time) | -| Breaking API changes | Add new fields, keep existing unchanged | - ---- - -## Tech Stack Integration - -### Backend Patterns (CLAUDE.md compliant) -- ✅ SQLModel + Alembic migrations -- ✅ Pydantic v2 schemas -- ✅ Service layer pattern (logic in services, not routers) -- ✅ Type hints + docstrings - -### Frontend Patterns (CLAUDE.md compliant) -- ✅ Vue 3 Composition API -- ✅ PrimeVue components -- ✅ Shared CSS patterns (`.roa-card`, `.roa-metric`) -- ✅ No `:deep()` selectors - -### Testing Patterns -- ✅ pytest for backend -- ✅ >90% coverage target -- ✅ Integration tests with real data - ---- - -## Next Steps - -1. **Review specification** → `/mnt/e/proiecte/roa2web/.auto-build/specs/bon-ocr-validation/spec.md` -2. **Create feature branch** → `feature/bon-ocr-validation` -3. **Implement Phase 1** → Validation engine + tests (Day 1) -4. **Implement Phase 2** → OCR integration (Day 2) -5. **Implement Phase 3** → Frontend + testing (Day 3) -6. **Deploy to staging** → Test with production receipts -7. **Monitor for 1 week** → Verify no regressions -8. **Deploy to production** → Roll out gradually - ---- - -**Estimated Completion:** 2026-01-02 (3 working days) -**Status:** Ready for Implementation diff --git a/.auto-build/specs/bon-ocr-validation/plan.md b/.auto-build/specs/bon-ocr-validation/plan.md deleted file mode 100644 index 8346daf..0000000 --- a/.auto-build/specs/bon-ocr-validation/plan.md +++ /dev/null @@ -1,439 +0,0 @@ -# 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.py` with base classes - - Define `ValidationRule` abstract base class with `validate()` method - - Define `ValidationResult` dataclass (is_valid, confidence_penalty, message) - - Add module docstring and imports -- **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: - - 1. **AmountRangeRule** - Check 0.01 ≤ amount ≤ 100,000 RON - 2. **TVARatioRule** - Check TVA is 5-24% of TOTAL - 3. **PaymentSumRule** - Check CARD + NUMERAR = TOTAL (±0.02 tolerance) - 4. **TVAEntriesSumRule** - Check Σ(TVA entries) = TVA TOTAL (±0.02) - 5. **CUIFormatRule** - Check RO + 6-10 digits format - 6. **CUIChecksumRule** - Romanian CIF Mod 11 checksum algorithm - 7. **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 `OCRValidationEngine` class - - 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) - -- **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.Image` method - - 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 - -- **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.py` - - `backend/modules/data_entry/schemas/ocr.py` -- **Lines**: ~50 lines modified, ~30 added -- **Description**: - - **In ocr_extractor.py:** - - Add fields to `ExtractionResult` dataclass (after existing fields): - ```python - # 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})'` - - **In schemas/ocr.py:** - - Add `ValidationWarning` schema: - ```python - class ValidationWarning(BaseModel): - field: str - severity: str # "warning" | "error" - message: str - ``` - - Add to `ExtractionData` schema (line ~57): - ```python - needs_manual_review: bool = False - validation_warnings: list[ValidationWarning] = [] - ``` - -- **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)` to `self._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): - 1. Get both Light and Medium values - 2. Run validation on both values - 3. Apply confidence penalties from validation results - 4. Choose value with ADJUSTED confidence (not raw) - 5. 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 - -- **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 `OCRResponse` schema to include validation fields: - ```python - needs_manual_review: bool = False - validation_warnings: list[ValidationWarning] = [] - confidence_info: dict[str, float] = {} # field -> adjusted confidence - ``` - - In `/process-receipt` endpoint (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 - -- **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 `receipts` table: - ```python - op.add_column('receipts', - sa.Column('needs_manual_review', sa.Boolean(), nullable=True, default=False) - ) - ``` - - Add downgrade to remove column - - Test migration: `alembic upgrade head` then `alembic downgrade -1` - -- **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 - -- **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: - - 1. **Start backend services:** - - SSH tunnel: `./ssh-tunnel-prod.sh start` - - Backend: `./start-backend.sh` - - 2. **Upload Five-Holding receipt:** - - File: `docs/data-entry/igiena 14 decembrie five-holding.pdf` - - Use `/api/ocr/process-receipt` endpoint - - 3. **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 - - 4. **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%) - - 5. **Test other receipts (regression):** - - Upload 3-5 other receipts from `docs/data-entry/` - - Verify no new false positives - - Verify existing correct extractions still work - - 6. **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: -1. Revert migration: `alembic downgrade -1` -2. Revert code changes: `git revert {commit}` -3. Fallback to Light + Tesseract only (skip Medium) -4. Add feature flag: `OCR_VALIDATION_ENABLED=false` - ---- - -**Plan Created:** 2025-12-30T17:25:00Z -**Ready for Implementation:** Yes diff --git a/.auto-build/specs/bon-ocr-validation/qa-report.md b/.auto-build/specs/bon-ocr-validation/qa-report.md deleted file mode 100644 index a592239..0000000 --- a/.auto-build/specs/bon-ocr-validation/qa-report.md +++ /dev/null @@ -1,123 +0,0 @@ -# QA Review Report: bon-ocr-validation - -**Feature:** OCR Data Extraction Validation System -**Status:** PASSED (after 1 iteration) -**Date:** 2025-12-30 - ---- - -## Summary - -| Metric | Value | -|--------|-------| -| Total issues found | 12 | -| Issues fixed | 9 (5 errors + 4 warnings) | -| Issues skipped | 3 (info level) | -| Files reviewed | 8 | -| Files modified | 5 | -| Tests passed | 37/37 (100%) | - ---- - -## Issues Fixed - -### Errors (5) - -1. **TypeError risk in payment sum calculation** (ocr_service.py:253-256) - - **Problem:** Decimal to float conversion could fail with empty lists or TypeError - - **Fix:** Added `safe_float()` and `safe_payment_sum()` helper functions with proper error handling - -2. **ZeroDivisionError risk** (validation.py:163) - - **Problem:** Missing zero-check before TVA ratio division - - **Fix:** Added explicit check: `if amount <= 0: return ValidationResult(...)` - -3. **Type safety in validation** (validation.py:163) - - **Problem:** No validation that dict values are numeric before math operations - - **Fix:** Added type check: `if not isinstance(amount, (int, float)): return ...` - -4. **Schema mismatch** (ocr.py:69) - - **Problem:** `needs_manual_review: bool` didn't match nullable database column - - **Fix:** Changed to `needs_manual_review: Optional[bool] = None` - -5. **Loose type annotations** (ocr_extractor.py:46) - - **Problem:** `dict` type annotation for `inter_ocr_ratios` lacked type parameters - - **Fix:** Changed to `dict[str, float]` - -### Warnings (4) - -1. **Manual review logic too strict** (validation.py:658) - - **Problem:** All warnings triggered manual review, even minor ones - - **Fix:** Only flag for review on high-severity warnings (Amount Range, Payment Sum, Inter-OCR) - -2. **Hardcoded field lists** (validation.py:596/619) - - **Problem:** Duplicated hardcoded field lists in multiple locations - - **Fix:** Replaced with `rule_field_map` dict that maps rule names to relevant fields - -3. **Validator re-instantiation** (ocr_service.py:246) - - **Status:** Deferred - minimal performance impact (~10ms) - -4. **Unverified CUI in test** (test_ocr_validation.py:279) - - **Problem:** Test used unverified CUI example - - **Fix:** Added algorithm verification comments with step-by-step checksum calculation - ---- - -## Issues Skipped (Info Level - 3) - -1. **Migration dependency verification** - Requires manual check with `alembic history` -2. **Debug print() statements** - Will be converted to logging in future refactor -3. **Medium preprocessing documentation** - Low priority, code is self-explanatory - ---- - -## Test Results - -``` -backend/modules/data_entry/tests/test_ocr_validation.py -======================== 37 passed, 1 warning in 1.39s ========================= -``` - -### Test Coverage - -| Category | Tests | Status | -|----------|-------|--------| -| AmountRangeRule | 4 | PASSED | -| TVARatioRule | 6 | PASSED | -| PaymentSumRule | 4 | PASSED | -| TVAEntriesSumRule | 3 | PASSED | -| CUIFormatRule | 6 | PASSED | -| CUIChecksumRule | 3 | PASSED | -| InterOCRConsistencyRule | 3 | PASSED | -| OCRValidationEngine | 6 | PASSED | -| Integration | 2 | PASSED | - ---- - -## Files Modified - -| File | Changes | -|------|---------| -| `validation.py` | Type safety, zero-division fix, manual review logic | -| `ocr_service.py` | Safe type conversions for validation data | -| `ocr.py` | Optional[bool] for needs_manual_review | -| `ocr_extractor.py` | Proper type annotations | -| `test_ocr_validation.py` | Fixed CUI test, added edge case tests | - ---- - -## Recommendations - -1. **Convert print() to logging** - Replace debug statements with `logger.debug()` -2. **Add singleton pattern** - Make OCRValidationEngine a class-level singleton for performance -3. **Migration verification** - Run `alembic history --verbose` before production deploy - ---- - -## Conclusion - -The bon-ocr-validation feature is **production-ready** after QA fixes. All critical issues have been resolved, type safety has been improved, and all 37 tests pass. - -**Next Steps:** -1. Run `/ab:memory-save` to save learnings -2. Commit changes with proper message -3. Deploy to staging for final manual testing diff --git a/.auto-build/specs/bon-ocr-validation/spec.md b/.auto-build/specs/bon-ocr-validation/spec.md deleted file mode 100644 index 405d502..0000000 --- a/.auto-build/specs/bon-ocr-validation/spec.md +++ /dev/null @@ -1,1533 +0,0 @@ -# Feature Specification: OCR Data Extraction Validation System - -**Feature ID:** bon-ocr-validation -**Priority:** Critical (P0 - Production Bug) -**Complexity:** High -**Estimated Effort:** 2-3 days -**Created:** 2025-12-30 -**Module:** Data Entry (backend/modules/data_entry/) - ---- - -## Overview - -Fix critical OCR data extraction issue where PaddleOCR Heavy preprocessing (88% confidence) overwrites correct Light OCR (98% confidence) data with garbage values, causing 10,000x magnitude errors in production receipts. - -**Value Proposition:** Prevent incorrect financial data from entering the system, reduce manual corrections, improve user trust in OCR accuracy. - ---- - -## Problem Statement - -### Current Behavior (BROKEN) - -The OCR processing pipeline (`backend/modules/data_entry/services/ocr_service.py`) uses a 3-step adaptive approach: -1. **Step 1:** PaddleOCR + Light preprocessing (fast, high confidence) -2. **Step 2:** PaddleOCR + Heavy preprocessing (faded receipts) -3. **Step 3:** Tesseract (complement missing fields only) - -**Critical Bug:** The `_merge_extractions()` method (lines 240-386) blindly prefers higher OCR confidence scores WITHOUT validating actual extracted values. - -### Real Production Example (Five-Holding Receipt) - -| Field | Light OCR (98%) ✅ | Heavy OCR (88%) ❌ | Final Result ❌ | -|-------|-------------------|-------------------|-----------------| -| **TOTAL** | 85.99 LEI | 859,762.16 LEI | **859,762.16** (10,000x error!) | -| **TVA** | 14.92 LEI | 149,214.92 LEI | **149,214.92** (10,000x error!) | -| **CUI** | R010562600 | (not found) | R010562600 | -| **Date** | 2025-10-11 | 2025-10-11 | 2025-10-11 | -| **Confidence** | 98% | 88% | 88% (wrong source!) | - -**Root Cause:** Heavy preprocessing causes digit concatenation on high-quality PDFs. The binarization and morphological operations (lines 153-164 in `image_preprocessor.py`) merge adjacent numbers, creating garbage values. - -### Impact - -- **Data Integrity:** Incorrect amounts enter accounting system -- **User Trust:** Users lose confidence in OCR accuracy -- **Manual Work:** Requires manual verification of ALL OCR extractions -- **Financial Risk:** Wrong amounts could be approved without review - ---- - -## User Stories - -### 1. As a user uploading a clear PDF receipt -**I want** OCR to extract correct values from the first pass -**So that** I don't have to manually correct obvious errors - -**Acceptance Criteria:** -- Light OCR correctly extracts 85.99 LEI (not 859,762.16) -- Heavy OCR is skipped when Light OCR confidence >= 90% -- No 10,000x magnitude errors - -### 2. As a user submitting a receipt with warnings -**I want** to be able to save receipts with validation warnings -**So that** I can submit for review even if OCR isn't perfect - -**Acceptance Criteria:** -- Save button works with warnings (not blocked) -- Receipt marked with `needs_manual_review=True` -- Warnings displayed clearly in UI - -### 3. As a supervisor reviewing receipts -**I want** to see which receipts need manual review -**So that** I can prioritize validation efforts - -**Acceptance Criteria:** -- Filter by "Needs Review" flag -- Validation warnings shown in detail view -- Clear indication of which fields are suspicious - -### 4. As a system validating cross-field data -**I want** to validate CARD + NUMERAR = TOTAL -**So that** payment methods match the total amount - -**Acceptance Criteria:** -- Cross-validation: sum of payment methods = TOTAL (±0.02 RON tolerance) -- If mismatch, flag for review -- Auto-correct TOTAL from payment sum if confidence < 80% - -### 5. As a system validating TVA entries -**I want** to validate Σ(TVA entries) = TVA TOTAL -**So that** individual TVA lines match the total TVA - -**Acceptance Criteria:** -- Cross-validation: sum of TVA entries = TVA TOTAL (±0.02 RON tolerance) -- TVA rate validation (5-24% of TOTAL) -- If mismatch, flag for review - ---- - -## Functional Requirements - -### Core Requirements (Must-Have) - -#### 1. Multi-Layer Validation Pipeline - -**FR-1.1:** Absolute value sanity checks -- Amount range: 0.01 - 100,000 RON -- Max 2 decimal places -- Date: not in future, not older than 10 years (2015+) -- CUI: 6-10 digits, valid Mod 11 checksum - -**FR-1.2:** Cross-field correlation validation -- TVA: 5-24% of TOTAL amount (Romanian rates: 5%, 9%, 11%, 19%, 21%) -- Payment methods: CARD + NUMERAR = TOTAL (±0.02 RON tolerance) -- Inter-OCR consistency: flag if values differ >10x between engines - -**FR-1.3:** Auto-correction logic -- If TOTAL is obviously wrong (>10x payment sum), use payment sum -- If TVA > TOTAL, recalculate TOTAL from TVA using reverse formula -- Preserve high-confidence values from Light OCR over low-confidence Heavy OCR - -**FR-1.4:** Validation result structure -```python -@dataclass -class ValidationResult: - is_valid: bool - warnings: List[ValidationWarning] # Non-blocking issues - errors: List[ValidationError] # Blocking issues (none for now) - corrected_fields: Dict[str, Any] # Auto-corrected values - needs_manual_review: bool # Flag for supervisor -``` - -#### 2. Replace Heavy with Medium OCR - -**FR-2.1:** Remove `preprocess_heavy()` method -- Current Heavy: aggressive binarization causes digit concatenation -- Reason: Destroys high-quality PDFs while trying to recover faded receipts - -**FR-2.2:** Add `preprocess_medium()` method -- Moderate contrast enhancement (CLAHE clipLimit=2.0) -- Light denoising (fastNlMeansDenoising h=6) -- NO binarization, NO morphological operations -- Preserve text boundaries on clear images - -**FR-2.3:** Update OCR pipeline -- Step 1: Light preprocessing (unchanged) -- Step 2: **Medium** preprocessing (replaces Heavy) -- Step 3: Tesseract (unchanged) - -#### 3. Enhanced CUI Extraction - -**FR-3.1:** Romanian CIF validation algorithm -- Implement Mod 11 checksum validation -- Control digit formula: `sum(digit[i] * weight[i]) % 11` -- Weights: `[7, 5, 3, 2, 1, 7, 5, 3, 2]` (right-to-left) - -**FR-3.2:** CUI format normalization -- Always add "RO" prefix if missing -- Remove spaces, dashes, dots -- Validate length: 6-10 digits - -**FR-3.3:** Improved regex patterns -```python -# Add OCR-tolerant patterns (current patterns are too strict) -CUI_OCR_TOLERANT_PATTERNS = [ - r'CIF[:\s]*R[O0]?\s*(\d[\d\s]{5,9})', # Spaces in CUI - r'C[I1]F[:\s]*(\d[\d\s]{6,10})', # C1F (I→1 OCR error) - r'C\.?\s*[I1]\.?\s*F\.?[:\s]*(\d+)', # C. I. F. (spaced) -] -``` - -#### 4. User Requirements Integration - -**FR-4.1:** Non-blocking validation warnings -- Save button enabled even with warnings -- User can override and submit -- Warnings displayed clearly in UI - -**FR-4.2:** Manual review flag -- Database field: `receipts.needs_manual_review` (BOOLEAN) -- Set to `TRUE` if: - - Any validation warning present - - Overall confidence < 85% - - Cross-validation fails - -**FR-4.3:** Apply to new uploads only -- No reprocessing of existing receipts -- Validation runs on OCR extraction (POST /api/ocr/extract) -- Migration: add column with default NULL (not FALSE) - -### Secondary Requirements (Nice-to-Have) - -**FR-S1:** Validation confidence scoring -- Each validation rule contributes to score -- Overall validation confidence: weighted average -- Display in UI alongside OCR confidence - -**FR-S2:** Validation rule configurability -- Move hardcoded thresholds to config -- Allow per-company customization -- Admin UI to adjust rules - ---- - -## Technical Requirements - -### Files to Create - -#### 1. `backend/modules/data_entry/services/ocr/validation.py` -**Purpose:** Validation utilities and rule engine -**Size:** ~400 lines -**Key Classes:** -- `ValidationRule` (base class) -- `AmountRangeRule`, `TVARatioRule`, `PaymentSumRule`, `CUIChecksumRule` -- `OCRValidationEngine` (orchestrator) - -**Example:** -```python -@dataclass -class ValidationWarning: - """Non-blocking validation warning.""" - field: str - rule: str - message: str - severity: str # 'low', 'medium', 'high' - suggested_value: Optional[Any] = None - -class ValidationRule(ABC): - """Base validation rule.""" - @abstractmethod - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - pass - -class AmountRangeRule(ValidationRule): - """Validate amount is in reasonable range (0.01 - 100,000 RON).""" - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - warnings = [] - if extraction.amount: - if extraction.amount < Decimal('0.01'): - warnings.append(ValidationWarning( - field='amount', - rule='amount_range', - message=f'Amount {extraction.amount} is too small (< 0.01 RON)', - severity='high' - )) - elif extraction.amount > Decimal('100000'): - warnings.append(ValidationWarning( - field='amount', - rule='amount_range', - message=f'Amount {extraction.amount} exceeds limit (> 100,000 RON)', - severity='high' - )) - return warnings - -class OCRValidationEngine: - """Orchestrate all validation rules.""" - def __init__(self): - self.rules = [ - AmountRangeRule(), - TVARatioRule(), - PaymentSumRule(), - InterOCRConsistencyRule(), - CUIChecksumRule(), - DateValidityRule(), - ] - - def validate(self, extraction: ExtractionResult) -> ValidationResult: - """Run all validation rules and return result.""" - all_warnings = [] - corrected_fields = {} - - for rule in self.rules: - warnings = rule.validate(extraction) - all_warnings.extend(warnings) - - # Apply auto-corrections - corrections = rule.auto_correct(extraction) - corrected_fields.update(corrections) - - needs_review = ( - len(all_warnings) > 0 or - extraction.overall_confidence < 0.85 - ) - - return ValidationResult( - is_valid=True, # Never block (warnings only) - warnings=all_warnings, - errors=[], - corrected_fields=corrected_fields, - needs_manual_review=needs_review - ) -``` - -#### 2. `backend/modules/data_entry/tests/test_ocr_validation.py` -**Purpose:** Unit tests for validation rules -**Size:** ~300 lines -**Coverage Target:** >90% - -**Test Cases:** -- `test_amount_range_valid()` - 85.99 RON passes -- `test_amount_range_too_high()` - 859,762.16 fails -- `test_tva_ratio_valid()` - 14.92/85.99 = 17.3% passes -- `test_tva_ratio_too_high()` - 149,214.92/859,762.16 = 17.3% but amounts wrong -- `test_payment_sum_matches()` - CARD 50 + NUMERAR 35.99 = TOTAL 85.99 -- `test_cui_checksum_valid()` - R010562600 passes Mod 11 -- `test_cui_checksum_invalid()` - R010562601 fails Mod 11 -- `test_inter_ocr_consistency()` - 85.99 vs 859,762.16 = 10,000x flag - -#### 3. `backend/modules/data_entry/tests/test_ocr_validation_integration.py` -**Purpose:** Integration tests with full OCR pipeline -**Size:** ~200 lines - -**Test Cases:** -- `test_five_holding_receipt()` - Real production case (85.99 not 859,762.16) -- `test_clear_pdf_uses_light_ocr()` - High-quality PDF skips Heavy -- `test_faded_receipt_uses_medium_ocr()` - Thermal receipt uses Medium -- `test_validation_warnings_in_response()` - API returns warnings -- `test_manual_review_flag_set()` - Flag set when confidence < 85% - -### Files to Modify - -#### 1. `backend/modules/data_entry/services/ocr_service.py` -**Changes:** ~200 lines modified, ~100 lines added - -**Key Modifications:** - -**A. Replace `_merge_extractions()` (lines 240-386) with validation-aware version:** -```python -def _merge_extractions( - self, - light: Optional[ExtractionResult], - medium: Optional[ExtractionResult] # Renamed from 'tesseract' -) -> ExtractionResult: - """ - Merge extractions with VALIDATION-AWARE logic. - - NEW Strategy: - 1. Run validation on both extractions - 2. Prefer extraction with FEWER warnings (not just higher confidence) - 3. For each field, pick value that passes validation - 4. Flag inter-OCR inconsistencies (>10x difference) - """ - from backend.modules.data_entry.services.ocr.validation import OCRValidationEngine - - validator = OCRValidationEngine() - - # Validate both extractions - light_validation = validator.validate(light) if light else None - medium_validation = validator.validate(medium) if medium else None - - result = ExtractionResult() - - # === AMOUNT (with validation check) === - if light.amount and medium.amount: - # Check for 10x inconsistency - ratio = max(light.amount, medium.amount) / min(light.amount, medium.amount) - if ratio > 10: - print(f"[Merge] WARNING: Inter-OCR inconsistency: {light.amount} vs {medium.amount} ({ratio:.0f}x)", flush=True) - # Prefer value that passes validation - light_warnings = [w for w in light_validation.warnings if w.field == 'amount'] - medium_warnings = [w for w in medium_validation.warnings if w.field == 'amount'] - - if len(light_warnings) < len(medium_warnings): - result.amount = light.amount - result.confidence_amount = light.confidence_amount - print(f"[Merge] Using Light OCR amount: {light.amount} (fewer warnings)", flush=True) - else: - result.amount = medium.amount - result.confidence_amount = medium.confidence_amount - print(f"[Merge] Using Medium OCR amount: {medium.amount} (fewer warnings)", flush=True) - else: - # Normal merge: prefer higher confidence - if light.confidence_amount >= medium.confidence_amount: - result.amount = light.amount - result.confidence_amount = light.confidence_amount - else: - result.amount = medium.amount - result.confidence_amount = medium.confidence_amount - elif light.amount: - result.amount = light.amount - result.confidence_amount = light.confidence_amount - elif medium.amount: - result.amount = medium.amount - result.confidence_amount = medium.confidence_amount - - # ... (similar logic for other fields) - - return result -``` - -**B. Add `preprocess_medium()` call (replace Heavy):** -```python -# Line ~130: Replace preprocess_heavy with preprocess_medium -print("=" * 60, flush=True) -print("[OCR] STEP 2: PaddleOCR + Medium preprocessing", flush=True) -print("=" * 60, flush=True) -medium_img = self.preprocessor.preprocess_medium(image) # NEW - -try: - paddle_medium = self.ocr_engine._paddle_recognize(medium_img) - # ... rest of processing -``` - -**C. Add validation to final result:** -```python -# Line ~204: Add validation before returning -if extraction: - extraction = self._final_validation(extraction) - - # NEW: Run validation engine - from backend.modules.data_entry.services.ocr.validation import OCRValidationEngine - validator = OCRValidationEngine() - validation_result = validator.validate(extraction) - - # Apply auto-corrections - for field, value in validation_result.corrected_fields.items(): - setattr(extraction, field, value) - - # Store validation warnings (add to ExtractionResult) - extraction.validation_warnings = validation_result.warnings - extraction.needs_manual_review = validation_result.needs_manual_review -``` - -#### 2. `backend/modules/data_entry/services/ocr_extractor.py` -**Changes:** ~50 lines modified, ~30 lines added - -**Key Modifications:** - -**A. Add validation fields to `ExtractionResult` (lines 10-50):** -```python -@dataclass -class ExtractionResult: - """Structured extraction result from receipt.""" - # ... existing fields ... - - # NEW: Validation results - validation_warnings: List[dict] = field(default_factory=list) # List of warnings - needs_manual_review: bool = False # Flag for supervisor review - - # NEW: Inter-OCR comparison data - inter_ocr_ratio: Optional[float] = None # Ratio between Light/Heavy values - inter_ocr_source_used: Optional[str] = None # 'light' or 'medium' -``` - -**B. Fix CLIENT CUI patterns (lines 253-272):** -```python -# Current patterns are too strict - add OCR-tolerant versions -CLIENT_CUI_PATTERNS = [ - # ... existing patterns ... - - # NEW: OCR-tolerant patterns - (r'CLIENT\s+C[I1UO]F\s*[:/]?\s*(?:R[O0])?(\d[\d\s]{5,9})', 0.96), # Spaces in CUI - (r'C[I1]F\s+CLIENT\s*[:/]?\s*(?:R[O0])?(\d[\d\s]{5,9})', 0.96), # Reversed format - (r'CLIENT.*?(?:R[O0])?(\d{6,10})\s*\n', 0.90), # CUI on next line -] -``` - -**C. Add CUI normalization and validation:** -```python -def _normalize_cui(self, cui: Optional[str]) -> Optional[str]: - """Normalize CUI format and validate checksum.""" - if not cui: - return None - - # Remove non-digits - digits = re.sub(r'\D', '', cui) - - # Validate length - if not (6 <= len(digits) <= 10): - return None - - # Validate Mod 11 checksum (Romanian CIF algorithm) - if not self._validate_cui_checksum(digits): - print(f"[CUI Validation] Invalid checksum: {digits}", flush=True) - return None - - # Add RO prefix - return f"RO{digits}" - -def _validate_cui_checksum(self, digits: str) -> bool: - """Validate Romanian CIF Mod 11 checksum.""" - if len(digits) < 2: - return False - - # Weights: 7, 5, 3, 2, 1, 7, 5, 3, 2 (right-to-left) - weights = [7, 5, 3, 2, 1, 7, 5, 3, 2] - - # Get control digit (last digit) - control = int(digits[-1]) - - # Calculate checksum (all digits except last) - digits_to_check = digits[:-1].zfill(9) # Pad with zeros if needed - checksum = sum(int(d) * w for d, w in zip(digits_to_check, weights)) - - # Mod 11 - remainder = checksum % 11 - expected_control = 0 if remainder == 10 else remainder - - return control == expected_control -``` - -#### 3. `backend/modules/data_entry/services/image_preprocessor.py` -**Changes:** ~80 lines added - -**Key Modifications:** - -**A. Add `preprocess_medium()` method (after line 166):** -```python -def preprocess_medium(self, image: np.ndarray) -> np.ndarray: - """ - Medium preprocessing for MIXED-QUALITY images. - Balance between Light (too gentle) and Heavy (too aggressive). - - Use cases: - - Moderately faded receipts - - Photos with uneven lighting - - Scans with slight blur - - Preprocessing steps: - - Moderate contrast enhancement (CLAHE clipLimit=2.0) - - Light denoising (fastNlMeansDenoising h=6) - - Gentle sharpening - - NO binarization (preserves text boundaries) - - NO morphological operations (avoids digit concatenation) - """ - # 0. Add safety padding - image = self._add_safety_padding(image) - - # 1. Grayscale - if len(image.shape) == 3: - gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) - else: - gray = image.copy() - - # 2. Scale (same as Light) - height, width = gray.shape - max_side = max(height, width) - if max_side > 4000: - scale = 4000 / max_side - gray = cv2.resize(gray, None, fx=scale, fy=scale, interpolation=cv2.INTER_AREA) - height, width = gray.shape - - if width < 1500: - scale = 1500 / width - new_width = int(width * scale) - new_height = int(height * scale) - if max(new_width, new_height) > 4000: - scale = 4000 / max(new_width, new_height) - gray = cv2.resize(gray, None, fx=scale, fy=scale, interpolation=cv2.INTER_CUBIC) - - # 3. Deskew - gray = self._deskew(gray) - - # 4. Moderate contrast enhancement - clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8)) - enhanced = clahe.apply(gray) - - # 5. Light denoising (less aggressive than Heavy) - denoised = cv2.fastNlMeansDenoising(enhanced, h=6, templateWindowSize=7, searchWindowSize=15) - - # 6. Gentle sharpening - gaussian = cv2.GaussianBlur(denoised, (0, 0), 1.0) - sharpened = cv2.addWeighted(denoised, 1.3, gaussian, -0.3, 0) - - # NO binarization, NO morphological operations - # This preserves text boundaries and avoids digit concatenation - return sharpened -``` - -**B. Mark `preprocess_heavy()` as deprecated:** -```python -def preprocess_heavy(self, image: np.ndarray) -> np.ndarray: - """ - Heavy preprocessing for FADED thermal receipts. - - ⚠️ DEPRECATED: Use preprocess_medium() instead. - Heavy preprocessing causes digit concatenation on clear PDFs. - Kept for backward compatibility only. - """ - # ... existing code (unchanged) -``` - -#### 4. `backend/modules/data_entry/routers/ocr.py` -**Changes:** ~40 lines modified - -**Key Modifications:** - -**A. Update `ExtractionData` schema instantiation (lines 106-128):** -```python -# Add validation warnings to response -validation_warnings_list = [ - { - 'field': w.field, - 'rule': w.rule, - 'message': w.message, - 'severity': w.severity, - 'suggested_value': w.suggested_value - } - for w in result.validation_warnings -] if hasattr(result, 'validation_warnings') else [] - -data = ExtractionData( - # ... existing fields ... - - # NEW: Validation fields - validation_warnings=validation_warnings_list, - needs_manual_review=getattr(result, 'needs_manual_review', False), - inter_ocr_ratio=getattr(result, 'inter_ocr_ratio', None), - inter_ocr_source_used=getattr(result, 'inter_ocr_source_used', None), -) -``` - -#### 5. `backend/modules/data_entry/schemas/ocr.py` -**Changes:** ~20 lines added - -**Key Modifications:** - -**A. Add validation fields to `ExtractionData` (after line 57):** -```python -class ValidationWarning(BaseModel): - """Validation warning from OCR extraction.""" - field: str = Field(description="Field name (e.g., 'amount', 'tva_total')") - rule: str = Field(description="Rule name (e.g., 'amount_range', 'tva_ratio')") - message: str = Field(description="Human-readable warning message") - severity: str = Field(description="Severity: 'low', 'medium', 'high'") - suggested_value: Optional[Any] = Field(default=None, description="Suggested corrected value") - -class ExtractionData(BaseModel): - """Extracted receipt data from OCR.""" - # ... existing fields ... - - # NEW: Validation results - validation_warnings: List[ValidationWarning] = Field(default=[], description="Validation warnings") - needs_manual_review: bool = Field(default=False, description="Flag for supervisor review") - inter_ocr_ratio: Optional[float] = Field(default=None, description="Ratio between OCR engines (>10 = inconsistent)") - inter_ocr_source_used: Optional[str] = Field(default=None, description="OCR engine used: 'light' or 'medium'") -``` - -#### 6. Database Migration: `backend/modules/data_entry/migrations/versions/XXX_add_needs_manual_review.py` -**Purpose:** Add `needs_manual_review` column to `receipts` table -**Size:** ~30 lines (Alembic migration) - -```python -"""Add needs_manual_review flag to receipts - -Revision ID: XXX -Create Date: 2025-12-30 -""" -from alembic import op -import sqlalchemy as sa - -revision = 'XXX' -down_revision = 'YYY' # Previous migration -branch_labels = None -depends_on = None - -def upgrade(): - # Add column with default NULL (not FALSE) - # NULL = not validated yet (old receipts) - # FALSE = validated, no review needed - # TRUE = validated, needs review - op.add_column('receipts', sa.Column('needs_manual_review', sa.Boolean(), nullable=True)) - -def downgrade(): - op.drop_column('receipts', 'needs_manual_review') -``` - -### Frontend Integration Points - -#### 1. `src/modules/data-entry/views/receipts/ReceiptCreateView.vue` -**Changes:** Display validation warnings below OCR results - -**Example:** -```vue - - - -``` - -#### 2. `src/modules/data-entry/components/ocr/OCRPreview.vue` -**Changes:** Add inter-OCR consistency indicator - -**Example:** -```vue - -``` - ---- - -## Design Decisions - -### 1. Why Validation Warnings Instead of Errors? - -**Decision:** Use non-blocking warnings instead of blocking errors. - -**Rationale:** -- User requirement: "Allow save with warnings" -- OCR will never be 100% perfect -- Users can override incorrect extractions -- Supervisor review catches issues before approval - -**Trade-off:** Risk of bad data entering system vs. user frustration with blocked submissions. - -**Mitigation:** Manual review flag ensures supervisor catches issues. - -### 2. Why Replace Heavy with Medium OCR? - -**Decision:** Remove Heavy preprocessing, add Medium preprocessing. - -**Rationale:** -- **Heavy causes digit concatenation** on clear PDFs (production evidence) -- Binarization destroys text boundaries on high-quality images -- Morphological operations merge adjacent numbers (85.99 → 859,762.16) - -**Analysis of Heavy Preprocessing (lines 153-164 in `image_preprocessor.py`):** -```python -# 7. Adaptive thresholding (binarization) - PROBLEM! -binary = cv2.adaptiveThreshold( - sharpened, 255, - cv2.ADAPTIVE_THRESH_GAUSSIAN_C, - cv2.THRESH_BINARY, - blockSize=11, C=5 # Block size can merge nearby digits -) - -# 8. Morphological operations - COMPOUNDS THE PROBLEM! -kernel_close = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2)) -result = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel_close) -# MORPH_CLOSE fills small gaps → merges adjacent numbers -``` - -**Alternative Considered:** Keep Heavy but add safeguards. **Rejected:** Too risky, no benefit for clear PDFs. - -### 3. Why Romanian CIF Mod 11 Validation? - -**Decision:** Implement CIF checksum validation algorithm. - -**Rationale:** -- Romanian CIFs have built-in checksum (last digit) -- Validates extracted CUI is mathematically correct -- Catches OCR digit errors (10562600 vs 10562601) - -**Algorithm:** Mod 11 checksum -- Weights: [7, 5, 3, 2, 1, 7, 5, 3, 2] (right-to-left) -- Formula: `sum(digit[i] * weight[i]) % 11` -- Control digit: remainder (0 if remainder=10) - -**Example:** RO10562600 -- Digits: 1,0,5,6,2,6,0,0,[0] -- Checksum: 1×7 + 0×5 + 5×3 + 6×2 + 2×1 + 6×7 + 0×5 + 0×3 = 7+0+15+12+2+42+0+0 = 78 -- 78 % 11 = 1 ≠ 0 → **INVALID!** (This CUI fails validation) - -**Note:** Some older CIFs may not have checksums (pre-2000). Validation is permissive (warning, not error). - -### 4. Why Apply to New Uploads Only? - -**Decision:** Don't reprocess existing receipts. - -**Rationale:** -- Migration impact: ~500 existing receipts in DB -- Reprocessing cost: OCR is slow (~2-5s per receipt) -- Risk: May change existing approved data -- Benefit: Minimal (old receipts already reviewed) - -**Implementation:** Migration adds column with default NULL (not FALSE). - ---- - -## Validation Rules Specification - -### 1. Amount Range Validation - -**Rule:** Amount must be between 0.01 and 100,000 RON. - -**Implementation:** -```python -class AmountRangeRule(ValidationRule): - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - warnings = [] - if extraction.amount: - if extraction.amount < Decimal('0.01'): - warnings.append(ValidationWarning( - field='amount', - rule='amount_range', - message=f'Amount {extraction.amount} is too small (< 0.01 RON)', - severity='high' - )) - elif extraction.amount > Decimal('100000'): - warnings.append(ValidationWarning( - field='amount', - rule='amount_range', - message=f'Amount {extraction.amount} exceeds limit (> 100,000 RON)', - severity='high' - )) - - # Check decimal places - decimal_places = abs(extraction.amount.as_tuple().exponent) - if decimal_places > 2: - warnings.append(ValidationWarning( - field='amount', - rule='decimal_places', - message=f'Amount has {decimal_places} decimal places (max 2)', - severity='medium', - suggested_value=extraction.amount.quantize(Decimal('0.01')) - )) - return warnings -``` - -**Test Cases:** -- 0.00 RON → Warning (too small) -- 0.01 RON → Valid -- 85.99 RON → Valid -- 100,000 RON → Valid -- 100,001 RON → Warning (too large) -- 859,762.16 RON → Warning (too large) -- 85.999 RON → Warning (too many decimals) - -### 2. TVA Ratio Validation - -**Rule:** TVA must be 5-24% of TOTAL amount. - -**Implementation:** -```python -class TVARatioRule(ValidationRule): - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - warnings = [] - if extraction.tva_total and extraction.amount: - # TVA cannot be greater than TOTAL - if extraction.tva_total > extraction.amount: - warnings.append(ValidationWarning( - field='tva_total', - rule='tva_greater_than_total', - message=f'TVA ({extraction.tva_total}) cannot be greater than TOTAL ({extraction.amount})', - severity='high', - suggested_value=None # Will be auto-corrected by service - )) - else: - # Check ratio - ratio = extraction.tva_total / extraction.amount * Decimal('100') - if ratio < Decimal('5'): - warnings.append(ValidationWarning( - field='tva_total', - rule='tva_ratio_low', - message=f'TVA is {ratio:.1f}% of total (expected 5-24%)', - severity='medium' - )) - elif ratio > Decimal('24'): - warnings.append(ValidationWarning( - field='tva_total', - rule='tva_ratio_high', - message=f'TVA is {ratio:.1f}% of total (expected 5-24%)', - severity='high' - )) - return warnings -``` - -**Test Cases:** -- TVA=14.92, TOTAL=85.99 → 17.3% → Valid -- TVA=149,214.92, TOTAL=859,762.16 → 17.3% → Both values wrong (caught by amount_range) -- TVA=4.00, TOTAL=100.00 → 4% → Warning (too low) -- TVA=100.00, TOTAL=85.99 → 116% → Warning (impossible!) - -### 3. Payment Sum Validation - -**Rule:** CARD + NUMERAR must equal TOTAL (±0.02 RON tolerance). - -**Implementation:** -```python -class PaymentSumRule(ValidationRule): - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - warnings = [] - if extraction.payment_methods and extraction.amount: - payment_sum = sum(pm['amount'] for pm in extraction.payment_methods) - difference = abs(payment_sum - extraction.amount) - - if difference > Decimal('0.02'): - warnings.append(ValidationWarning( - field='amount', - rule='payment_sum_mismatch', - message=f'Payment methods sum ({payment_sum}) ≠ TOTAL ({extraction.amount}), diff={difference}', - severity='high', - suggested_value=payment_sum - )) - return warnings - - def auto_correct(self, extraction: ExtractionResult) -> Dict[str, Any]: - """Auto-correct TOTAL from payment sum if confidence < 80%.""" - corrections = {} - if extraction.payment_methods and extraction.amount: - payment_sum = sum(pm['amount'] for pm in extraction.payment_methods) - difference = abs(payment_sum - extraction.amount) - - if difference > Decimal('0.02') and extraction.confidence_amount < 0.80: - corrections['amount'] = payment_sum - print(f"[Auto-Correct] TOTAL corrected: {extraction.amount} → {payment_sum} (from payment methods)", flush=True) - return corrections -``` - -**Test Cases:** -- CARD=50, NUMERAR=35.99, TOTAL=85.99 → Valid -- CARD=50, NUMERAR=35.97, TOTAL=85.99 → Diff=0.02 → Valid (tolerance) -- CARD=50, NUMERAR=35.00, TOTAL=85.99 → Diff=0.99 → Warning - -### 4. TVA Entries Sum Validation - -**Rule:** Σ(TVA entries) must equal TVA TOTAL (±0.02 RON tolerance). - -**Implementation:** -```python -class TVAEntriesSumRule(ValidationRule): - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - warnings = [] - if extraction.tva_entries and extraction.tva_total: - entries_sum = sum(e['amount'] for e in extraction.tva_entries) - difference = abs(entries_sum - extraction.tva_total) - - if difference > Decimal('0.02'): - warnings.append(ValidationWarning( - field='tva_total', - rule='tva_entries_sum_mismatch', - message=f'TVA entries sum ({entries_sum}) ≠ TVA TOTAL ({extraction.tva_total}), diff={difference}', - severity='medium', - suggested_value=entries_sum - )) - return warnings - - def auto_correct(self, extraction: ExtractionResult) -> Dict[str, Any]: - """Use entries sum as TVA TOTAL if mismatch.""" - corrections = {} - if extraction.tva_entries and extraction.tva_total: - entries_sum = sum(e['amount'] for e in extraction.tva_entries) - difference = abs(entries_sum - extraction.tva_total) - - if difference > Decimal('0.02'): - corrections['tva_total'] = entries_sum - print(f"[Auto-Correct] TVA TOTAL corrected: {extraction.tva_total} → {entries_sum} (from entries)", flush=True) - return corrections -``` - -**Test Cases:** -- Entries=[A:19%:14.92], TOTAL=14.92 → Valid -- Entries=[A:19%:10.00, B:9%:4.92], TOTAL=14.92 → Valid -- Entries=[A:19%:14.92], TOTAL=14.94 → Diff=0.02 → Valid (tolerance) -- Entries=[A:19%:14.92], TOTAL=15.00 → Diff=0.08 → Warning - -### 5. Inter-OCR Consistency Validation - -**Rule:** Flag if values differ >10x between OCR engines. - -**Implementation:** -```python -class InterOCRConsistencyRule(ValidationRule): - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - """This rule is applied during merge, stores ratio in extraction.""" - warnings = [] - if hasattr(extraction, 'inter_ocr_ratio') and extraction.inter_ocr_ratio: - if extraction.inter_ocr_ratio > 10: - warnings.append(ValidationWarning( - field='amount', - rule='inter_ocr_inconsistency', - message=f'Large inconsistency between OCR engines ({extraction.inter_ocr_ratio:.0f}x difference)', - severity='high' - )) - return warnings -``` - -**Test Cases:** -- Light=85.99, Medium=86.00 → Ratio=1.00 → Valid -- Light=85.99, Medium=90.00 → Ratio=1.05 → Valid -- Light=85.99, Medium=859.76 → Ratio=10.00 → Valid (edge case) -- Light=85.99, Medium=859,762.16 → Ratio=10,000 → Warning! - -### 6. CUI Checksum Validation - -**Rule:** Validate Romanian CIF Mod 11 checksum. - -**Implementation:** -```python -class CUIChecksumRule(ValidationRule): - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - warnings = [] - if extraction.cui: - # Normalize CUI - digits = re.sub(r'\D', '', extraction.cui) - - # Validate length - if not (6 <= len(digits) <= 10): - warnings.append(ValidationWarning( - field='cui', - rule='cui_length', - message=f'CUI length invalid: {len(digits)} digits (expected 6-10)', - severity='medium' - )) - return warnings - - # Validate Mod 11 checksum - if not self._validate_checksum(digits): - warnings.append(ValidationWarning( - field='cui', - rule='cui_checksum', - message=f'CUI checksum invalid: {extraction.cui} (failed Mod 11 validation)', - severity='medium' # Medium: some old CIFs don't have checksums - )) - return warnings - - def _validate_checksum(self, digits: str) -> bool: - """Romanian CIF Mod 11 checksum validation.""" - if len(digits) < 2: - return False - - weights = [7, 5, 3, 2, 1, 7, 5, 3, 2] - control = int(digits[-1]) - digits_to_check = digits[:-1].zfill(9) - - checksum = sum(int(d) * w for d, w in zip(digits_to_check, weights)) - remainder = checksum % 11 - expected = 0 if remainder == 10 else remainder - - return control == expected -``` - -**Test Cases:** -- R010562600 → Checksum validation -- R011201891 → Checksum validation -- R012345678 → Warning (invalid checksum) -- R01234 → Warning (too short) - -### 7. Date Validity Validation - -**Rule:** Date must not be in future, not older than 10 years. - -**Implementation:** -```python -class DateValidityRule(ValidationRule): - def validate(self, extraction: ExtractionResult) -> List[ValidationWarning]: - warnings = [] - if extraction.receipt_date: - today = date.today() - - # Check future date - if extraction.receipt_date > today: - warnings.append(ValidationWarning( - field='receipt_date', - rule='date_future', - message=f'Date is in the future: {extraction.receipt_date}', - severity='high' - )) - - # Check too old (10 years) - cutoff_date = today.replace(year=today.year - 10) - if extraction.receipt_date < cutoff_date: - warnings.append(ValidationWarning( - field='receipt_date', - rule='date_too_old', - message=f'Date is older than 10 years: {extraction.receipt_date}', - severity='medium' - )) - return warnings -``` - -**Test Cases:** -- 2025-12-30 (today) → Valid -- 2025-10-11 → Valid -- 2026-01-01 → Warning (future) -- 2015-12-31 → Valid (exactly 10 years) -- 2014-12-31 → Warning (too old) - ---- - -## Acceptance Criteria - -### Critical Success Criteria (Must Pass) - -✅ **AC-1:** Five-Holding receipt extracts correct values -- **Given:** Production PDF receipt (Five-Holding, 85.99 LEI) -- **When:** OCR processes with new validation -- **Then:** - - TOTAL = 85.99 LEI (NOT 859,762.16) - - TVA = 14.92 LEI (NOT 149,214.92) - - CUI = R010562600 - - Overall confidence >= 90% - -✅ **AC-2:** Save works with validation warnings -- **Given:** Receipt with low confidence (75%) -- **When:** User clicks Save -- **Then:** - - Warnings displayed in UI - - Save button enabled - - Receipt saved with `needs_manual_review=TRUE` - -✅ **AC-3:** Cross-validation: CARD + NUMERAR = TOTAL -- **Given:** Receipt with CARD=50, NUMERAR=35.99 -- **When:** OCR extracts TOTAL=85.98 (off by 0.01) -- **Then:** - - Warning displayed: "Payment sum (85.99) ≠ TOTAL (85.98)" - - Suggested value: 85.99 - - Auto-corrected if confidence < 80% - -✅ **AC-4:** Cross-validation: Σ(TVA entries) = TVA TOTAL -- **Given:** Receipt with TVA A=10.00, TVA B=4.92 -- **When:** OCR extracts TVA TOTAL=14.90 (off by 0.02) -- **Then:** - - Warning displayed: "TVA entries sum (14.92) ≠ TVA TOTAL (14.90)" - - Auto-corrected to 14.92 - -✅ **AC-5:** CUI Mod 11 validation works -- **Given:** Receipt with CUI R010562600 -- **When:** OCR processes -- **Then:** - - CUI validated against Mod 11 checksum - - If invalid, warning displayed - - Format normalized to "RO" prefix - -### Secondary Criteria (Nice-to-Have) - -🔲 **AC-S1:** Medium OCR performs better than Heavy -- **Given:** 10 clear PDF receipts -- **When:** Processed with Light → Medium → Tesseract -- **Then:** - - No 10x magnitude errors - - Average confidence >= 90% - - Processing time < 5s - -🔲 **AC-S2:** Validation warnings show in UI -- **Given:** Receipt with 3 validation warnings -- **When:** OCR completes -- **Then:** - - Warning section displayed - - Each warning shows: field, message, severity - - Suggested values displayed if available - ---- - -## Testing Strategy - -### Unit Tests (~300 lines) - -**File:** `backend/modules/data_entry/tests/test_ocr_validation.py` - -**Test Coverage:** -```python -# Amount validation -test_amount_range_valid() -test_amount_range_too_small() -test_amount_range_too_large() -test_amount_decimal_places() - -# TVA validation -test_tva_ratio_valid() -test_tva_ratio_too_low() -test_tva_ratio_too_high() -test_tva_greater_than_total() -test_tva_entries_sum_matches() -test_tva_entries_sum_mismatch() - -# Payment validation -test_payment_sum_matches() -test_payment_sum_mismatch_within_tolerance() -test_payment_sum_mismatch_auto_corrected() - -# CUI validation -test_cui_checksum_valid() -test_cui_checksum_invalid() -test_cui_length_invalid() -test_cui_normalization() - -# Date validation -test_date_valid() -test_date_future() -test_date_too_old() - -# Inter-OCR consistency -test_inter_ocr_consistency_valid() -test_inter_ocr_consistency_10x_difference() - -# Validation engine -test_validation_engine_no_warnings() -test_validation_engine_multiple_warnings() -test_validation_engine_auto_corrections() -test_needs_manual_review_flag() -``` - -### Integration Tests (~200 lines) - -**File:** `backend/modules/data_entry/tests/test_ocr_validation_integration.py` - -**Test Coverage:** -```python -# Real receipts -test_five_holding_receipt() # Production case (85.99 not 859,762.16) -test_omv_receipt() # Clear PDF, Light OCR only -test_kaufland_receipt() # Faded thermal, Medium OCR -test_mega_image_receipt() # Multiple TVA entries - -# OCR pipeline -test_light_ocr_high_confidence_skips_medium() -test_light_ocr_low_confidence_runs_medium() -test_medium_ocr_replaces_heavy() -test_validation_runs_after_merge() - -# API responses -test_api_returns_validation_warnings() -test_api_returns_needs_manual_review_flag() -test_api_returns_inter_ocr_ratio() -test_api_auto_corrects_amount_from_payments() - -# Edge cases -test_no_ocr_engines_available() -test_pdf_with_multiple_pages() -test_receipt_with_no_tva() -test_receipt_with_no_payment_methods() -``` - -### Manual Testing Checklist - -1. **Upload Five-Holding receipt PDF** (production case) - - [ ] Verify TOTAL = 85.99 (not 859,762.16) - - [ ] Verify TVA = 14.92 (not 149,214.92) - - [ ] Verify no validation warnings - - [ ] Verify overall confidence >= 90% - -2. **Upload faded thermal receipt photo** - - [ ] Verify Medium OCR used (not Heavy) - - [ ] Verify readable text extracted - - [ ] Verify no digit concatenation - -3. **Upload receipt with payment methods** - - [ ] Verify CARD + NUMERAR displayed - - [ ] Verify sum matches TOTAL - - [ ] If mismatch, verify warning displayed - -4. **Upload receipt with multiple TVA entries** - - [ ] Verify all TVA entries extracted - - [ ] Verify sum matches TVA TOTAL - - [ ] If mismatch, verify warning displayed - -5. **Submit receipt with warnings** - - [ ] Verify Save button enabled - - [ ] Verify warnings displayed in UI - - [ ] Verify `needs_manual_review` flag set - -6. **Filter receipts by "Needs Review"** - - [ ] Verify filter shows flagged receipts - - [ ] Verify supervisor can review - ---- - -## Risks and Mitigations - -| Risk | Likelihood | Impact | Mitigation | -|------|------------|--------|------------| -| **Medium OCR still causes errors** | Medium | High | Keep Tesseract as Step 3 fallback; validation catches issues | -| **CUI Mod 11 validation too strict** | Medium | Low | Use warning (not error); allow override; some old CIFs don't have checksums | -| **Validation rules too permissive** | Low | Medium | Start conservative, tune based on production data | -| **Validation rules too strict** | Medium | Low | Non-blocking warnings allow user override | -| **Performance impact** | Low | Low | Validation is fast (<10ms); OCR dominates processing time | -| **Breaking changes to API** | Low | High | Add new fields, keep existing fields unchanged; frontend optional | -| **Database migration issues** | Low | Medium | Use NULL default (not FALSE); test on staging first | - ---- - -## Out of Scope - -**Explicitly NOT included in this feature:** - -1. ❌ **Reprocessing existing receipts** - Only new uploads validated -2. ❌ **Machine learning OCR improvements** - Use existing PaddleOCR/Tesseract -3. ❌ **Custom OCR training** - Generic models only -4. ❌ **Approval workflow changes** - Validation is separate from approval -5. ❌ **Automatic approval** - Always requires supervisor review -6. ❌ **Advanced validation rules** - Only basic sanity checks -7. ❌ **Multi-currency support** - RON only for now -8. ❌ **Historical receipt validation** - Phase 2 feature -9. ❌ **OCR confidence tuning** - Accept engine defaults -10. ❌ **Frontend validation logic** - Backend only (frontend displays) - ---- - -## Open Questions - -### Q1: Should we keep Heavy preprocessing as fallback? - -**Answer:** No. Remove completely. Evidence shows it causes more harm than good on clear PDFs. Medium preprocessing handles mixed-quality images better. - -### Q2: What tolerance for payment sum validation? - -**Answer:** ±0.02 RON (2 cents). Romanian receipts use 2 decimal places. This handles rounding errors. - -### Q3: Should CUI validation be blocking or warning? - -**Answer:** Warning only. Some old Romanian CIFs (pre-2000) don't have Mod 11 checksums. Also, OCR may extract digits incorrectly. - -### Q4: What if Light OCR has high confidence but wrong values? - -**Answer:** Validation catches this. If Light OCR extracts 859,762.16 with 98% confidence, amount_range rule flags it (>100,000 limit). User sees warning. - -### Q5: Should we reprocess existing receipts with new validation? - -**Answer:** No. Too risky and time-consuming. Apply to new uploads only. If user wants to re-validate old receipt, they can re-upload. - -### Q6: What about receipts with no payment methods? - -**Answer:** No validation warning. Not all receipts show CARD/NUMERAR breakdown (especially older thermal receipts). Only validate if payment methods are extracted. - -### Q7: Should validation auto-correct or just warn? - -**Answer:** Both. Auto-correct obvious errors (TOTAL from payment sum if confidence < 80%). Warn for ambiguous cases. Never silently change high-confidence values. - -### Q8: How to handle receipts from future (clock skew)? - -**Answer:** Warning only (not error). Allow up to 1 day in future (±24h tolerance) for clock skew. Beyond that, warn user. - ---- - -## Estimated Complexity - -**Overall:** High -**Justification:** - -- **File Count:** 6 modified, 3 created, 1 migration = 10 files -- **Line Changes:** ~1,135 lines (400 new validation, 300 tests, 200 integration tests, 235 modifications) -- **Risk Level:** Medium (core OCR pipeline changes, but validation is additive) -- **Testing:** 15-20 new test cases, manual testing required -- **Dependencies:** None (uses existing OCR engines) -- **Complexity Factors:** - - Multi-layer validation logic - - Romanian CIF checksum algorithm - - Cross-field validation dependencies - - Inter-OCR comparison logic - - Auto-correction logic - - Frontend integration - - Database migration - -**Estimated Effort:** 2-3 days -- Day 1: Validation engine + unit tests -- Day 2: OCR pipeline integration + medium preprocessing -- Day 3: Frontend integration + manual testing + bug fixes - ---- - -## Dependencies - -### External Libraries -- ✅ `cv2` (OpenCV) - Already installed -- ✅ `numpy` - Already installed -- ✅ `paddleocr` - Already installed -- ✅ `tesseract` - Already installed -- ✅ `pydantic` - Already installed -- ✅ `sqlalchemy` - Already installed - -### Internal Modules -- ✅ `backend/modules/data_entry/services/ocr_service.py` -- ✅ `backend/modules/data_entry/services/ocr_extractor.py` -- ✅ `backend/modules/data_entry/services/image_preprocessor.py` -- ✅ `backend/modules/data_entry/routers/ocr.py` -- ✅ `backend/modules/data_entry/schemas/ocr.py` -- ✅ `backend/modules/data_entry/db/models/receipt.py` - -### Database Schema Changes -- ✅ Add `needs_manual_review` column to `receipts` table (nullable BOOLEAN) -- ✅ Alembic migration required - ---- - -## Implementation Notes - -### Priority Order (Recommended) - -1. **Phase 1: Core Validation (Day 1)** - - Create `ocr/validation.py` module - - Implement validation rules (amount, TVA, payment, CUI, date) - - Write unit tests - - **Checkpoint:** All tests pass - -2. **Phase 2: OCR Integration (Day 2 Morning)** - - Add `preprocess_medium()` to image_preprocessor - - Update `_merge_extractions()` with validation-aware logic - - Remove/deprecate `preprocess_heavy()` - - **Checkpoint:** Five-Holding receipt extracts correctly - -3. **Phase 3: API Updates (Day 2 Afternoon)** - - Update `ExtractionResult` dataclass with validation fields - - Update API schemas (ocr.py, routers/ocr.py) - - Add database migration - - **Checkpoint:** API returns validation warnings - -4. **Phase 4: Integration Testing (Day 3 Morning)** - - Write integration tests - - Test with real receipts (Five-Holding, OMV, Kaufland) - - **Checkpoint:** All integration tests pass - -5. **Phase 5: Frontend & Polish (Day 3 Afternoon)** - - Update Vue components to display warnings - - Add "Needs Review" filter - - Manual testing - - Bug fixes - - **Checkpoint:** Production-ready - -### Code Quality Standards - -- ✅ Type hints for all functions -- ✅ Docstrings for all public methods -- ✅ Unit test coverage >90% -- ✅ Integration tests for critical paths -- ✅ Print statements for debugging (will be converted to logging later) -- ✅ Follow existing code patterns (SQLModel, Pydantic v2, FastAPI) - -### Performance Considerations - -- **Validation overhead:** <10ms per receipt (negligible vs. OCR time) -- **Medium preprocessing:** Similar speed to Heavy (~500ms) -- **Database migration:** Non-blocking (adds NULL column) -- **Frontend impact:** Minimal (only displays warnings) - ---- - -## Related Documentation - -### Project Context -- **CLAUDE.md:** Data Entry module instructions -- **docs/data-entry/DATA-ENTRY-MODULE.md:** Module architecture -- **docs/ARCHITECTURE-DECISIONS.md:** Ultrathin monolith rationale - -### Technical References -- **Romanian CIF validation:** https://ro.wikipedia.org/wiki/Cod_de_identificare_fiscal%C4%83 -- **OpenCV preprocessing:** https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html -- **PaddleOCR docs:** https://github.com/PaddlePaddle/PaddleOCR - -### Similar Features -- **Payment methods extraction:** Already implemented in `ocr_extractor.py:1361` -- **TVA entries extraction:** Already implemented in `ocr_extractor.py:820` -- **Cross-validation logic:** Pattern from `_cross_validate_and_calculate_amount` (lines 468-557) - ---- - -## Summary - -This specification provides a comprehensive solution to fix critical OCR data extraction issues in the Data Entry module. The multi-layer validation system ensures data integrity while maintaining user flexibility through non-blocking warnings. - -**Key Benefits:** -- ✅ Prevents 10,000x magnitude errors (85.99 vs 859,762.16) -- ✅ Validates cross-field dependencies (payment sum, TVA sum) -- ✅ Improves CUI extraction with Mod 11 checksum -- ✅ Replaces problematic Heavy OCR with Medium preprocessing -- ✅ Non-blocking warnings preserve user workflow -- ✅ Manual review flag helps supervisors prioritize - -**Next Steps:** -1. Review and approve specification -2. Create feature branch: `feature/bon-ocr-validation` -3. Implement Phase 1 (validation engine) -4. Continue with Phases 2-5 -5. Deploy to staging for testing -6. Monitor production for 1 week before full rollout - ---- - -**Document Version:** 1.0 -**Last Updated:** 2025-12-30 -**Status:** Ready for Implementation -**Estimated Completion:** 2026-01-02 (3 working days) diff --git a/.auto-build/specs/bon-ocr-validation/status.json b/.auto-build/specs/bon-ocr-validation/status.json deleted file mode 100644 index f484aa0..0000000 --- a/.auto-build/specs/bon-ocr-validation/status.json +++ /dev/null @@ -1,158 +0,0 @@ -{ - "feature": "bon-ocr-validation", - "status": "QA_PASSED", - "created": "2025-12-30T17:19:00Z", - "updated": "2025-12-30T19:15:00Z", - "totalTasks": 11, - "currentTask": 11, - "tasksCompleted": 11, - "history": [ - { - "status": "SPEC_COMPLETE", - "at": "2025-12-30T17:19:00Z" - }, - { - "status": "PLANNING", - "at": "2025-12-30T17:25:00Z" - }, - { - "status": "PLANNING_COMPLETE", - "at": "2025-12-30T17:27:00Z" - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T17:28:00Z", - "task": 1, - "started": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T17:30:00Z", - "task": 1, - "title": "Create validation module structure", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T17:35:00Z", - "task": 2, - "title": "Implement validation rules (7 rules)", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:00:00Z", - "task": 3, - "started": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:05:00Z", - "task": 3, - "title": "Create validation engine orchestrator", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:10:00Z", - "task": 4, - "started": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:15:00Z", - "task": 4, - "title": "Write unit tests for validation", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:20:00Z", - "task": 5, - "started": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:25:00Z", - "task": 5, - "title": "Add Medium OCR preprocessing", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:30:00Z", - "task": 6, - "started": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:35:00Z", - "task": 6, - "title": "Update ExtractionResult schema", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:40:00Z", - "task": 7, - "started": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:50:00Z", - "task": 7, - "title": "Refactor merge_extractions with validation", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T18:55:00Z", - "task": 8, - "title": "Update API schemas", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T19:00:00Z", - "task": 9, - "started": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T19:05:00Z", - "task": 9, - "title": "Create database migration", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T19:10:00Z", - "task": 10, - "title": "Write integration tests", - "completed": true - }, - { - "status": "IMPLEMENTING", - "at": "2025-12-30T19:15:00Z", - "task": 11, - "title": "Test with Five-Holding receipt (manual testing guide created)", - "completed": true - }, - { - "status": "IMPLEMENTATION_COMPLETE", - "at": "2025-12-30T19:15:00Z" - }, - { - "status": "QA_REVIEW", - "at": "2025-12-30T20:00:00Z", - "issues_found": 12, - "issues_fixed": 9 - }, - { - "status": "QA_PASSED", - "at": "2025-12-30T20:30:00Z", - "iterations": 1, - "tests_passed": 37 - } - ] -} diff --git a/.auto-build/specs/telegram-trezorerie/SUMMARY.md b/.auto-build/specs/telegram-trezorerie/SUMMARY.md deleted file mode 100644 index 106509e..0000000 --- a/.auto-build/specs/telegram-trezorerie/SUMMARY.md +++ /dev/null @@ -1,58 +0,0 @@ -# Telegram Trezorerie Unification - Quick Summary - -## What We're Building -Replace two separate treasury buttons with one unified button showing complete treasury overview. - -## Key Changes - -### Menu (Before → After) -``` -BEFORE: -Row 2: [Sold Companie] [Trezorerie Casa] -Row 3: [Trezorerie Banca] [Sold Clienti] -Row 4: [Sold Furnizori] [Evolutie Incasari] - -AFTER: -Row 2: [Sold Companie] [Trezorerie] -Row 3: [Sold Clienti] [Sold Furnizori] -Row 4: [Evolutie Incasari] -``` - -### Message Format (New) -``` -Sold Total Trezorerie: 20,500 RON - -Casa -Sold Total Cash: 5,000 RON -Conturi de Casa: - - Casa Lei: 3,000 RON - - Casa Valuta: 2,000 RON - -Banca -Sold Total Banca: 15,500 RON -Conturi Bancare: - - BCR RON: 10,000 RON - - BRD EUR: 5,500 RON -``` - -## Files to Modify - -1. **formatters.py** - Add `format_treasury_combined_response()` -2. **menus.py** - Update `create_main_menu()` layout (lines 234-247) -3. **handlers.py** - Add `menu:trezorerie` callback case - -## Backward Compatibility - -Keep working: -- `/trezorerie_casa` - shows Casa only -- `/trezorerie_banca` - shows Banca only -- `/trezorerie` - shows unified view - -## Estimated Time -2.5 hours total (1h coding, 1h testing, 0.5h review) - -## Testing Focus -- Grand total = Casa + Banca -- Menu layout compaction -- Legacy commands still work -- Performance footer appears diff --git a/.auto-build/specs/telegram-trezorerie/plan.md b/.auto-build/specs/telegram-trezorerie/plan.md deleted file mode 100644 index eca707a..0000000 --- a/.auto-build/specs/telegram-trezorerie/plan.md +++ /dev/null @@ -1,106 +0,0 @@ -# Implementation Plan: telegram-trezorerie - -**Status**: ✅ COMPLETE -**Created**: 2025-12-30T18:45:00Z - -## Progress Tracker - -| Task | Status | Completed | -|------|--------|-----------| -| Task 1: Add unified formatter | ✅ Done | 2025-12-30 18:48 | -| Task 2: Update main menu layout | ✅ Done | 2025-12-30 18:49 | -| Task 3: Add callback handler | ✅ Done | 2025-12-30 18:50 | -| Task 4: Manual testing | ✅ Done | 2025-12-30 18:51 | - -## Tasks - -### Task 1: Add unified formatter -- **Status**: ✅ Done (2025-12-30 18:48) -- **Files**: `backend/modules/telegram/bot/formatters.py` -- **Description**: Add `format_treasury_combined_response()` function after line 187 (after `format_treasury_banca_response`). This new formatter will: - - Calculate grand total (casa + banca) - - Format unified message with three sections: Grand Total, Casa breakdown, Banca breakdown - - Follow existing patterns (Markdown bold, account lists, RON amounts with thousands separator) -- **Dependencies**: None - -### Task 2: Update main menu layout -- **Status**: ✅ Done (2025-12-30 18:49) -- **Files**: `backend/modules/telegram/bot/menus.py` -- **Description**: Update `create_main_menu()` function (lines 233-247) to: - - Replace 2-button rows (Trezorerie Casa + Trezorerie Banca) with single "Trezorerie" button - - Compact layout: Row 2 [Sold Companie][Trezorerie], Row 3 [Sold Clienti][Sold Furnizori], Row 4 [Evolutie Incasari] - - Use callback_data="menu:trezorerie" for new button -- **Dependencies**: None - -### Task 3: Add callback handler -- **Status**: ✅ Done (2025-12-30 18:50) -- **Files**: `backend/modules/telegram/bot/handlers.py` -- **Description**: Add `menu:trezorerie` case in `button_callback()` function after line 1485 (before existing casa/banca handlers). The handler will: - - Call `get_treasury_breakdown_split()` to get data - - Use new `format_treasury_combined_response()` formatter - - Add performance footer - - Display with action buttons -- **Dependencies**: Task 1 - -### Task 4: Manual testing -- **Status**: ✅ Done (2025-12-30 18:51) -- **Files**: None (testing only) -- **Description**: Test the implementation: - - Verify new menu layout shows single [Trezorerie] button - - Verify unified view shows grand total + Casa section + Banca section - - Verify grand total = Casa total + Banca total - - Verify legacy `/trezorerie_casa` and `/trezorerie_banca` commands still work - - Verify [Menu Principal] button returns to menu -- **Dependencies**: Tasks 1, 2, 3 - -## Implementation Notes - -### Existing Code Patterns - -**Formatter pattern** (from `format_treasury_casa_response`): -```python -def format_treasury_xxx_response(data: Dict[str, Any], company_name: str = None) -> str: - text = "" - total = round(data.get('total', 0)) - text += f"**Sold Total XXX:** {total:,} RON\n\n" - # ... account list - return text -``` - -**Menu button pattern** (from `create_main_menu`): -```python -InlineKeyboardButton("Button Text", callback_data="menu:action") -``` - -**Callback handler pattern** (from existing casa handler): -```python -elif action == "trezorerie": - from backend.modules.telegram.bot.helpers import get_treasury_breakdown_split - treasury_data = await get_treasury_breakdown_split(company['id'], jwt_token) - from backend.modules.telegram.bot.formatters import format_treasury_combined_response, add_performance_footer - from backend.modules.telegram.bot.menus import create_action_buttons, format_response_with_company - content = format_treasury_combined_response(treasury_data) - response = format_response_with_company(content, company['name']) - # ... performance footer - keyboard = create_action_buttons("trezorerie", show_export=False, show_refresh=False) - # ... edit message -``` - -### Data Structure - -The `get_treasury_breakdown_split()` helper returns: -```python -{ - 'casa': { - 'accounts': [{'name': str, 'balance': float, 'cont': str}, ...], - 'total': float - }, - 'banca': { - 'accounts': [{'name': str, 'balance': float, 'cont': str}, ...], - 'total': float - }, - 'cache_hit': bool, - 'response_time_ms': int, - 'cache_source': str | None -} -``` diff --git a/.auto-build/specs/telegram-trezorerie/spec.md b/.auto-build/specs/telegram-trezorerie/spec.md deleted file mode 100644 index b314523..0000000 --- a/.auto-build/specs/telegram-trezorerie/spec.md +++ /dev/null @@ -1,527 +0,0 @@ -# Feature: Telegram Unified Treasury Button - -## Overview - -Replace the two separate "Trezorerie Casa" and "Trezorerie Banca" buttons in the Telegram bot main menu with a single unified "Trezorerie" button that displays comprehensive treasury information in one message. This consolidation improves UX by reducing button clutter and providing a complete treasury overview at a glance. - -## Problem Statement - -Currently, users must tap two separate buttons ("Trezorerie Casa" and "Trezorerie Banca") to view complete treasury information. This creates friction in the user experience and takes up valuable menu real estate. Users need a single, comprehensive treasury view that shows: -- Grand total treasury (Casa + Banca combined) -- Casa total with account breakdown -- Banca total with account breakdown - -The unified view will reduce taps from 2 to 1 and free up menu space for future features. - -## User Stories - -- As a financial manager, I want to see all treasury data (Casa + Banca) in one message so that I can quickly assess total available funds without switching between views -- As a user, I want a cleaner, more compact menu so that I can navigate more efficiently -- As a power user, I want to optionally use the legacy `/trezorerie_casa` and `/trezorerie_banca` commands so that I can access specific views if needed -- As a developer, I want consistent formatting across all treasury messages so that maintenance is easier - -## Functional Requirements - -### Core Requirements - -1. **Single "Trezorerie" Button**: Replace [Trezorerie Casa] and [Trezorerie Banca] with a single [Trezorerie] button in main menu -2. **Combined Display Format**: Show unified message with: - - Grand Total (Casa + Banca) - - Casa section: total + all accounts - - Banca section: total + all accounts -3. **Menu Layout Compaction**: Reorganize main menu to fill the freed space: - - Row 2: [Sold Companie] [Trezorerie] - - Row 3: [Sold Clienti] [Sold Furnizori] - - Row 4: [Evolutie Incasari] -4. **Backward Compatibility**: Keep `/trezorerie`, `/trezorerie_casa`, `/trezorerie_banca` commands working -5. **Performance Footer**: Include cache hit/miss metadata in response (consistent with existing pattern) - -### Secondary Requirements - -1. **Export Support**: Add "Export" button (matching other financial views) -2. **Refresh Support**: Add "Refresh" button (matching other financial views) -3. **Error Handling**: Graceful fallback if treasury data unavailable - -## Technical Requirements - -### Files to Modify - -| File | Changes | -|------|---------| -| `backend/modules/telegram/bot/menus.py` | Update `create_main_menu()` (lines 234-247): Replace 2-button rows with unified layout | -| `backend/modules/telegram/bot/formatters.py` | Add `format_treasury_combined_response()` function after line 187 | -| `backend/modules/telegram/bot/handlers.py` | Update `button_callback()` (lines 1486-1546): Add `menu:trezorerie` case; Keep existing casa/banca cases for legacy commands | -| `backend/modules/telegram/bot/handlers.py` | Update `/trezorerie` command handler (if exists) to use new unified formatter, OR create new `trezorerie_unified_command()` | - -### New Files to Create - -None - all changes are modifications to existing files. - -### Dependencies - -- Existing: `get_treasury_breakdown_split()` from `helpers.py` (lines 275-354) -- Existing: `format_response_with_company()` from `menus.py` (lines 111-144) -- Existing: `create_action_buttons()` from `menus.py` (lines 278-335) -- Existing: `add_performance_footer()` from `formatters.py` - -### Database Changes - -None - uses existing `/api/reports/dashboard/treasury-breakdown` endpoint. - -### API Changes - -None - reuses existing backend API endpoints. - -## Design Decisions - -### Approach - -**Unified Formatter Pattern**: Create a new `format_treasury_combined_response()` function that: -1. Takes the full `treasury_data` dict (containing both `casa` and `banca` keys) -2. Calculates grand total by summing casa + banca totals -3. Formats a single message with three sections: Grand Total, Casa breakdown, Banca breakdown -4. Reuses existing formatting patterns (Markdown bold, account lists, RON amounts) - -**Menu Reorganization**: Compact the main menu layout to: -- Row 2: [Sold Companie] [Trezorerie] (unified button replaces Trezorerie Casa) -- Row 3: [Sold Clienti] [Sold Furnizori] (moves up from previous rows) -- Row 4: [Evolutie Incasari] (full width, moves up) - -This creates a balanced 2-2-1 button layout that's more compact than the previous 2-2-2 layout. - -**Callback Naming**: Use `menu:trezorerie` for the new unified button to maintain consistency with existing callback patterns (`menu:sold`, `menu:clienti`, etc.). - -### Alternatives Considered - -1. **Keep Both Buttons + Add Third**: Rejected because it increases menu clutter instead of reducing it -2. **Tabbed Interface**: Rejected because Telegram inline keyboards don't support tabs; would require complex state management -3. **Remove Legacy Commands**: Rejected to maintain backward compatibility for power users who have muscle memory for old commands - -## Acceptance Criteria - -### Menu Changes -- [ ] Main menu has single [Trezorerie] button instead of [Trezorerie Casa] and [Trezorerie Banca] -- [ ] Menu layout shows Row 2: [Sold Companie] [Trezorerie] -- [ ] Menu layout shows Row 3: [Sold Clienti] [Sold Furnizori] -- [ ] Menu layout shows Row 4: [Evolutie Incasari] (full width) - -### Message Format -- [ ] Unified message shows "Sold Total Trezorerie: X,XXX RON" at top -- [ ] Unified message shows "Casa" section with total and account list -- [ ] Unified message shows "Banca" section with total and account list -- [ ] Grand total equals sum of Casa total + Banca total -- [ ] All amounts rounded to whole RON (0 decimals) with thousands separator -- [ ] Company name displayed at top of message -- [ ] Performance footer shows cache hit/miss metadata - -### Functionality -- [ ] Tapping [Trezorerie] button displays unified treasury message -- [ ] Message includes [Refresh] and [Menu Principal] action buttons -- [ ] Legacy `/trezorerie_casa` command still works (shows Casa only) -- [ ] Legacy `/trezorerie_banca` command still works (Banca only) -- [ ] `/trezorerie` command shows unified view (if exists, otherwise create it) -- [ ] Callback `menu:trezorerie` triggers unified view -- [ ] Error handling works if treasury data unavailable - -### Code Quality -- [ ] No code duplication between formatters -- [ ] Consistent Markdown formatting with existing patterns -- [ ] Proper error logging in handlers -- [ ] Comments explain new unified formatter logic - -## Out of Scope - -- **Export Functionality**: While we add the Export button, implementing actual Excel/PDF export is out of scope (deferred to future feature) -- **Historical Trends**: No graph or historical data - current snapshot only -- **Currency Conversion**: RON only, no multi-currency support -- **Account Filtering**: Show all accounts, no user-selectable filters -- **Menu Help Text**: No changes to `/help` command text (can be updated separately) - -## Message Format Examples - -### Unified Treasury Message (New) - -``` -Five Holding SRL - -Sold Total Trezorerie: 20,500 RON - -Casa -Sold Total Cash: 5,000 RON - -Conturi de Casa: - - Casa Lei: 3,000 RON - - Casa Valuta: 2,000 RON - -Banca -Sold Total Banca: 15,500 RON - -Conturi Bancare: - - BCR RON: 10,000 RON - - BRD EUR: 5,500 RON - -[Cache HIT | L1 | 23ms] -``` - -### Casa Only Message (Legacy `/trezorerie_casa`) - -``` -Five Holding SRL - -Sold Total Cash: 5,000 RON - -Conturi de Casa: - - Casa Lei: 3,000 RON - - Casa Valuta: 2,000 RON - -[Cache HIT | L1 | 23ms] -``` - -### Banca Only Message (Legacy `/trezorerie_banca`) - -``` -Five Holding SRL - -Sold Total Banca: 15,500 RON - -Conturi Bancare: - - BCR RON: 10,000 RON - - BRD EUR: 5,500 RON - -[Cache HIT | L1 | 23ms] -``` - -## Implementation Details - -### 1. New Unified Formatter - -Add to `backend/modules/telegram/bot/formatters.py` after line 187: - -```python -def format_treasury_combined_response(data: Dict[str, Any], company_name: str = None) -> str: - """ - Format combined treasury data (Casa + Banca) for Telegram. - - Args: - data: Dict with 'casa' and 'banca' keys from get_treasury_breakdown_split() - company_name: Company name (kept for compatibility, not used) - - Returns: - Formatted Markdown string with grand total and both sections - - Example: - data = {'casa': {...}, 'banca': {...}} - text = format_treasury_combined_response(data) - """ - text = "" - - # Extract totals - casa_total = round(data.get('casa', {}).get('total', 0)) - banca_total = round(data.get('banca', {}).get('total', 0)) - grand_total = casa_total + banca_total - - # Grand total - text += f"**Sold Total Trezorerie:** {grand_total:,} RON\n\n" - - # Casa section - text += "**Casa**\n" - text += f"Sold Total Cash: {casa_total:,} RON\n\n" - - casa_accounts = data.get('casa', {}).get('accounts', []) - if casa_accounts: - text += "Conturi de Casa:\n" - for acc in casa_accounts: - name = acc.get('name', 'N/A') - balance = round(acc.get('balance', 0)) - text += f" - {name}: {balance:,} RON\n" - else: - text += "Nu exista conturi de casa.\n" - - text += "\n" - - # Banca section - text += "**Banca**\n" - text += f"Sold Total Banca: {banca_total:,} RON\n\n" - - banca_accounts = data.get('banca', {}).get('accounts', []) - if banca_accounts: - text += "Conturi Bancare:\n" - for acc in banca_accounts: - name = acc.get('name', 'N/A') - balance = round(acc.get('balance', 0)) - text += f" - {name}: {balance:,} RON\n" - else: - text += "Nu exista conturi bancare.\n" - - return text -``` - -### 2. Update Main Menu Layout - -Update `backend/modules/telegram/bot/menus.py` lines 234-247: - -```python -# Rows 2-4: Financial options (compacted layout) -keyboard.extend([ - [ - InlineKeyboardButton("Sold Companie", callback_data="menu:sold"), - InlineKeyboardButton("Trezorerie", callback_data="menu:trezorerie") - ], - [ - InlineKeyboardButton("Sold Clienti", callback_data="menu:clienti"), - InlineKeyboardButton("Sold Furnizori", callback_data="menu:furnizori") - ], - [ - InlineKeyboardButton("Evolutie Incasari", callback_data="menu:evolutie") - ] -]) -``` - -### 3. Update Button Callback Handler - -Update `backend/modules/telegram/bot/handlers.py` in `button_callback()` function, add new case after line 1485: - -```python -elif action == "trezorerie": - # Unified trezorerie (Casa + Banca combined) - from backend.modules.telegram.bot.helpers import get_treasury_breakdown_split - treasury_data = await get_treasury_breakdown_split(company['id'], jwt_token) - - from backend.modules.telegram.bot.formatters import format_treasury_combined_response, add_performance_footer - from backend.modules.telegram.bot.menus import create_action_buttons, format_response_with_company - - content = format_treasury_combined_response(treasury_data) - response = format_response_with_company(content, company['name']) - - # Add performance footer if cache metadata is available - if 'cache_hit' in treasury_data and 'response_time_ms' in treasury_data: - cache_hit = treasury_data['cache_hit'] - response_time_ms = treasury_data['response_time_ms'] - cache_source = treasury_data.get('cache_source', None) - response = add_performance_footer(response, cache_hit, response_time_ms, cache_source) - - keyboard = create_action_buttons("trezorerie", show_export=False, show_refresh=False) - - try: - await query.edit_message_text( - response, - reply_markup=keyboard, - parse_mode=ParseMode.MARKDOWN - ) - except Exception as e: - # Ignore "Message is not modified" error - if "Message is not modified" not in str(e): - raise - -elif action == "casa": - # Keep existing casa handler for legacy /trezorerie_casa command - # ... existing code ... -``` - -### 4. Legacy Command Handlers - -Keep existing handlers in `backend/modules/telegram/bot/handlers.py`: -- `trezorerie_casa_command()` (lines 884-955) - NO CHANGES -- `trezorerie_banca_command()` (lines 957-1028) - NO CHANGES - -Update `/trezorerie` command (or create if missing) to use unified formatter: - -```python -async def trezorerie_command(update: Update, context: ContextTypes.DEFAULT_TYPE): - """ - Handle /trezorerie command - shows unified treasury data (Casa + Banca). - - Displays complete treasury overview with grand total and account breakdowns. - - Args: - update: Telegram update object - context: Telegram context - """ - try: - telegram_user_id = update.effective_user.id - logger.info(f"/trezorerie command from user {telegram_user_id}") - - # Check linked - is_linked = await check_user_linked(telegram_user_id) - if not is_linked: - await update.message.reply_text( - "**Cont neconectat**\n\nFoloseste /start", - parse_mode=ParseMode.MARKDOWN - ) - return - - # Get active company - session_manager = get_session_manager() - from backend.modules.telegram.bot.helpers import get_active_company_or_prompt - company = await get_active_company_or_prompt(update, session_manager, telegram_user_id) - - if not company: - return # Prompt already sent - - # Get auth data - auth_data = await get_user_auth_data(telegram_user_id) - jwt_token = auth_data['jwt_token'] - - # Get treasury breakdown split - from backend.modules.telegram.bot.helpers import get_treasury_breakdown_split - treasury_data = await get_treasury_breakdown_split( - company_id=company['id'], - jwt_token=jwt_token - ) - - if not treasury_data: - await update.message.reply_text("Eroare la incarcarea trezoreriei.") - return - - # Format unified response - from backend.modules.telegram.bot.formatters import format_treasury_combined_response, add_performance_footer - from backend.modules.telegram.bot.menus import create_action_buttons, format_response_with_company - - content = format_treasury_combined_response(treasury_data) - response = format_response_with_company(content, company['name']) - - # Add performance footer if cache metadata is available - if 'cache_hit' in treasury_data and 'response_time_ms' in treasury_data: - cache_hit = treasury_data['cache_hit'] - response_time_ms = treasury_data['response_time_ms'] - cache_source = treasury_data.get('cache_source', None) - response = add_performance_footer(response, cache_hit, response_time_ms, cache_source) - - keyboard = create_action_buttons("trezorerie", show_export=True) - - await update.message.reply_text( - response, - reply_markup=keyboard, - parse_mode=ParseMode.MARKDOWN - ) - - except Exception as e: - logger.error(f"Error in trezorerie_command: {e}", exc_info=True) - await update.message.reply_text("Eroare la incarcarea trezoreriei.") -``` - -### 5. Command Registration - -Update `backend/modules/telegram/bot_main.py` - ensure `trezorerie_command` is registered (line 126): - -```python -application.add_handler(CommandHandler("trezorerie", trezorerie_command)) -``` - -No changes needed for `trezorerie_casa_command` and `trezorerie_banca_command` (already registered at lines 127-128). - -## Risks and Mitigations - -| Risk | Likelihood | Impact | Mitigation | -|------|------------|--------|------------| -| Users confused by menu change | Medium | Low | Keep legacy commands working; users can still use old commands if preferred | -| Grand total calculation error | Low | Medium | Add unit tests verifying `casa_total + banca_total = grand_total`; Use `round()` consistently | -| Message too long for Telegram | Low | Medium | Telegram limit is 4096 chars; current format uses ~300-500 chars; Monitor in production | -| Cache metadata missing | Low | Low | Graceful fallback: only add footer if metadata exists (existing pattern) | -| Formatting inconsistencies | Low | Low | Reuse existing formatters (`format_response_with_company`, `add_performance_footer`) | - -## Open Questions - -1. **Should `/trezorerie` show unified view or redirect to menu?** - - **Decision**: Show unified view (recommended for consistency) - - Rationale: More useful for power users who type commands - -2. **Should we add Export button functionality now or later?** - - **Decision**: Add button now, implement export functionality later - - Rationale: Maintains UI consistency with other views; export can be separate feature - -3. **Should we update `/help` command text to reflect menu changes?** - - **Decision**: Out of scope for this feature - - Rationale: Can be updated in separate UX improvement task - -## Testing Strategy - -### Manual Testing Checklist - -1. **Menu Navigation**: - - [ ] /menu shows new compact layout - - [ ] [Trezorerie] button exists in Row 2 - - [ ] [Trezorerie Casa] and [Trezorerie Banca] buttons removed - - [ ] [Sold Clienti] and [Sold Furnizori] in Row 3 - - [ ] [Evolutie Incasari] in Row 4 - -2. **Unified View**: - - [ ] Tapping [Trezorerie] shows combined message - - [ ] Grand total = Casa total + Banca total - - [ ] Casa section shows total + accounts - - [ ] Banca section shows total + accounts - - [ ] Company name at top - - [ ] Performance footer at bottom - -3. **Legacy Commands**: - - [ ] `/trezorerie_casa` shows Casa only - - [ ] `/trezorerie_banca` shows Banca only - - [ ] `/trezorerie` shows unified view - -4. **Action Buttons**: - - [ ] [Refresh] button exists (for command, not callback) - - [ ] [Menu Principal] button exists - - [ ] [Menu Principal] returns to main menu - -5. **Edge Cases**: - - [ ] No casa accounts: Shows "Nu exista conturi de casa" - - [ ] No banca accounts: Shows "Nu exista conturi bancare" - - [ ] Zero balances: Shows "0 RON" - - [ ] Large amounts: Thousands separator works (e.g., "1,234,567 RON") - -### Unit Testing - -```python -# Test unified formatter -def test_format_treasury_combined_response(): - data = { - 'casa': { - 'total': 5000.0, - 'accounts': [ - {'name': 'Casa Lei', 'balance': 3000.0}, - {'name': 'Casa Valuta', 'balance': 2000.0} - ] - }, - 'banca': { - 'total': 15500.0, - 'accounts': [ - {'name': 'BCR RON', 'balance': 10000.0}, - {'name': 'BRD EUR', 'balance': 5500.0} - ] - } - } - - result = format_treasury_combined_response(data) - - # Assert grand total - assert "20,500 RON" in result - - # Assert casa section - assert "Casa Lei: 3,000 RON" in result - assert "Casa Valuta: 2,000 RON" in result - - # Assert banca section - assert "BCR RON: 10,000 RON" in result - assert "BRD EUR: 5,500 RON" in result -``` - -## Estimated Complexity - -**Medium** - This is a straightforward refactoring task with clear requirements and existing patterns to follow. - -**Justification**: -- **Low Risk**: No database changes, no new API endpoints, uses existing data -- **Well-Defined**: Clear specification with examples and acceptance criteria -- **Existing Patterns**: Follows established formatter and handler patterns -- **Backward Compatible**: Legacy commands remain functional -- **Estimated Effort**: 2-3 hours (1h coding, 1h testing, 0.5h code review) - -**Complexity Breakdown**: -- New formatter function: 30 min (straightforward string formatting) -- Menu layout update: 10 min (simple button rearrangement) -- Callback handler: 20 min (copy-paste existing pattern) -- Legacy command update: 20 min (if `/trezorerie` needs changes) -- Testing: 60 min (manual testing + edge cases) -- Code review fixes: 30 min (buffer for feedback) - -**Total Estimated Time**: 2.5 hours diff --git a/.auto-build/specs/telegram-trezorerie/status.json b/.auto-build/specs/telegram-trezorerie/status.json deleted file mode 100644 index a877576..0000000 --- a/.auto-build/specs/telegram-trezorerie/status.json +++ /dev/null @@ -1,30 +0,0 @@ -{ - "feature": "telegram-trezorerie", - "status": "IMPLEMENTATION_COMPLETE", - "created_at": "2025-12-30T18:30:00Z", - "updated": "2025-12-30T18:51:00Z", - "totalTasks": 4, - "currentTask": 4, - "tasksCompleted": 4, - "estimated_complexity": "medium", - "estimated_hours": 2.5, - "files_affected": 3, - "requires_database_changes": false, - "requires_api_changes": false, - "backward_compatible": true, - "history": [ - {"status": "SPEC_DRAFT", "at": "2025-12-30T18:30:00Z"}, - {"status": "SPEC_COMPLETE", "at": "2025-12-30T18:35:00Z"}, - {"status": "PLANNING", "at": "2025-12-30T18:45:00Z"}, - {"status": "PLANNING_COMPLETE", "at": "2025-12-30T18:46:00Z"}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:47:00Z", "task": 1, "started": true}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:48:00Z", "task": 1, "title": "Add unified formatter", "completed": true}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:48:00Z", "task": 2, "started": true}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:49:00Z", "task": 2, "title": "Update main menu layout", "completed": true}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:49:00Z", "task": 3, "started": true}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:50:00Z", "task": 3, "title": "Add callback handler", "completed": true}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:50:00Z", "task": 4, "started": true}, - {"status": "IMPLEMENTING", "at": "2025-12-30T18:51:00Z", "task": 4, "title": "Manual testing", "completed": true}, - {"status": "IMPLEMENTATION_COMPLETE", "at": "2025-12-30T18:51:00Z"} - ] -} diff --git a/.beads/interactions.jsonl b/.beads/interactions.jsonl deleted file mode 100644 index e69de29..0000000 diff --git a/.beads/issues.jsonl b/.beads/issues.jsonl deleted file mode 100644 index e69de29..0000000 diff --git a/.gitignore b/.gitignore index 1cf6b9e..ef7ec00 100644 --- a/.gitignore +++ b/.gitignore @@ -433,15 +433,9 @@ run_tests.* scan_*.json sdist/ sdist/ -# Secrets directories (contains credentials, keys, passwords) secrets/ - # Allow documentation in secrets directories !**/secrets/README.md - -# SSH tunnel configuration (next to .env files) -backend/ssh-tunnels.json -!backend/ssh-tunnels.json.example security_*.json share/python-wheels/ sqlnet.ora @@ -531,26 +525,5 @@ backend/data/receipts/uploads/* backend/data/ocr_queue/ !backend/data/*/.gitkeep -# Auth trusted devices (conține date sensibile — nu commita!) -data/auth/trusted_devices.json - -# PRD tasks (generated, not tracked) -tasks/ - -# ============================================================================ -# 🤖 CLAUDE & RALPH AUTOMATION - DO NOT COMMIT -# ============================================================================ -# Claude handover and context files (session-specific) +# Handoff document (session continuity, not for version control) .claude/HANDOFF.md -.claude/handover/ -CONTEXT_HANDOVER_*.md - -# Ralph automation - ignore entire directory -scripts/ralph/ - -# ============================================================================ -# 💾 SQLITE RUNTIME FILES - DO NOT COMMIT -# ============================================================================ -# SQLite WAL (Write-Ahead Log) and SHM (Shared Memory) files -*.db-shm -*.db-wal