feat(ocr): Add modular store profiles with hot-reload support
## Store Profiles System
- Add ProfileRegistry for CUI-based profile lookup
- Add BaseStoreProfile with generic extraction patterns
- Implement hot-reload via POST /api/data-entry/ocr/profiles/reload
## 12 Store Profiles
- LIDL: Multi-rate TVA (A, B, C, D codes)
- OMV, SOCAR: B2B with client CUI, YYYY.MM.DD dates
- BRICK, DEDEMAN: Standard TVA, e-factura support
- KINETERRA, BEST PRINT: Non-VAT payers (returns [])
- STEPOUT MARKET: TVA 5% (books/reduced rate)
- UNLIMITED KEYS: NUMERAR payment detection
- GAMA INK, ELECTROBERING, PICTUS VELUM: Standard TVA
## Flexible TVA Patterns
- All patterns use (\d{1,2})% to accept any rate
- Supports historical (19%, 9%, 5%) and current (21%, 11%)
## Payment Methods Fix
- Fixed base.py to support multiple payments of same type
- Changed deduplication from method-only to (method, amount) tuple
- Returns separate entries for split payments
## Tools
- Add generate_store_profile.py for automatic profile generation
- Analyzes PDFs via OCR API and detects patterns
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
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backend/modules/data_entry/services/ocr/profiles/lidl.py
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backend/modules/data_entry/services/ocr/profiles/lidl.py
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"""
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LIDL store profile for OCR extraction.
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Lidl receipts have a specific TVA format without hyphen/colon separators:
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TOTAL TVA 9,84
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TVA A 21,00% 7,71
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TVA B 11,00% 2,13
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This profile handles multi-rate TVA extraction for Lidl receipts.
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"""
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import re
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from decimal import Decimal, InvalidOperation
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from typing import List, Dict, Any
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from .base import BaseStoreProfile
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from . import ProfileRegistry
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@ProfileRegistry.register
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class LidlProfile(BaseStoreProfile):
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"""
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LIDL DISCOUNT S.R.L. - multi-rate TVA profile.
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Key characteristics:
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- Multi-rate TVA (codes A, B, C, D with any percentage - patterns are flexible)
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- TVA format: "TVA A XX,XX% YY,YY" (code + percent + amount on same line)
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- Supports historical rates (19%, 9%, 5%) and current rates (21%, 11%)
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- CARD payment usually equals total
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- No client CUI on receipts
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"""
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CUI_LIST = ["22891860"]
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NAME_PATTERNS = ["LIDL", "LDL", "L1DL", "LIDL DISCOUNT"] # OCR variants
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STORE_NAME = "LIDL DISCOUNT S.R.L."
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# Lidl-specific TVA patterns
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# Format: "TVA A 21,00% 7,71" (code + percent + amount on same line)
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TVA_PATTERNS = [
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# Primary: "TVA A 21,00% 7.71" with various spacing
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r'T[VU][AR]\s+([A-D])\s+(\d{1,2})[.,]?\d{0,2}\s*%\s+([\d.,]+)',
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# With backslash OCR artifact: "TVA A \21,00% 7.71"
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r'T[VU][AR]\s+([A-D])\s+\\?(\d{1,2})[.,]?\d{0,2}\s*%\s+([\d.,]+)',
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# IVA variant (rare OCR misread)
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r'IVA\s+([A-D])\s+(\d{1,2})[.,]?\d{0,2}\s*%\s+([\d.,]+)',
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]
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def extract_tva_entries(self, text: str) -> List[dict]:
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"""
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Extract Lidl-specific TVA entries.
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Handles multiple TVA rates (A, B, C, D) commonly found on Lidl receipts.
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Uses deduplication to avoid counting the same entry twice from different patterns.
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Args:
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text: Raw OCR text from receipt
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Returns:
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List of TVA entries with code, percent, and amount
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"""
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entries = []
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seen = set() # Deduplication key: (code, percent)
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for pattern in self.TVA_PATTERNS:
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for match in re.finditer(pattern, text, re.IGNORECASE):
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try:
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code = match.group(1).upper()
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percent = int(match.group(2))
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amount = self._parse_decimal(match.group(3))
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if amount and amount > 0:
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entry_key = (code, percent)
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if entry_key not in seen:
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entries.append({
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'code': code,
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'percent': percent,
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'amount': amount
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})
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seen.add(entry_key)
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except (ValueError, InvalidOperation):
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continue
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return entries
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def get_validation_hints(self) -> Dict[str, Any]:
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"""Return Lidl-specific validation hints."""
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return {
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"has_multi_rate_tva": True,
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"card_equals_total": True,
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"has_client_cui": False,
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"has_efactura": False,
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"is_non_vat_payer": False,
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}
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