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| from typing import Dict, Any, Tuple, List | |
| import re | |
| from datetime import datetime | |
| from pydantic import BaseModel, Field | |
| class ValidationResult(BaseModel): | |
| is_valid: bool | |
| errors: List[str] = Field(default_factory=list) | |
| confidence_penalty: float = 0.0 | |
| def validate_extracted_fields(doc_class: str, fields: Dict[str, Any]) -> ValidationResult: | |
| """ | |
| Validates extracted field values based on business rules: | |
| - total_amount: numeric, > 0 | |
| - date / invoice_date: valid date pattern | |
| - invoice_number: non-empty string | |
| Returns ValidationResult with pass/fail and penalty. | |
| """ | |
| errors = [] | |
| penalty = 0.0 | |
| if doc_class in ["invoice", "receipt"]: | |
| amount_val = fields.get("total_amount") | |
| if amount_val is not None: | |
| # Clean currency symbols and commas | |
| cleaned_str = re.sub(r'[^\d.-]', '', str(amount_val).replace(',', '')) | |
| try: | |
| amt = float(cleaned_str) | |
| if amt <= 0: | |
| errors.append(f"total_amount must be positive: got {amt}") | |
| penalty += 0.25 | |
| except ValueError: | |
| errors.append(f"total_amount cannot be parsed as float: {amount_val}") | |
| penalty += 0.35 | |
| date_val = fields.get("date") or fields.get("invoice_date") | |
| if date_val is not None: | |
| # Check standard date formats | |
| valid_date = False | |
| date_str = str(date_val).strip() | |
| date_formats = ["%Y-%m-%d", "%d/%m/%Y", "%m/%d/%Y", "%d-%m-%Y", "%Y/%m/%d", "%b %d, %Y", "%d %b %Y"] | |
| for fmt in date_formats: | |
| try: | |
| datetime.strptime(date_str, fmt) | |
| valid_date = True | |
| break | |
| except ValueError: | |
| pass | |
| # Also check with date regex | |
| if not valid_date and not re.search(r'\d{1,4}[/\-.]\d{1,2}[/\-.]\d{1,4}', date_str): | |
| errors.append(f"date format unrecognized: {date_val}") | |
| penalty += 0.2 | |
| if doc_class == "invoice": | |
| inv_num = fields.get("invoice_number") | |
| if inv_num is not None and not str(inv_num).strip(): | |
| errors.append("invoice_number is empty") | |
| penalty += 0.3 | |
| is_valid = len(errors) == 0 | |
| return ValidationResult(is_valid=is_valid, errors=errors, confidence_penalty=min(penalty, 0.5)) | |