fund-tracer/backend/app/services/parser_service.py

"""Parse raw OCR / multimodal extraction results into TransactionRecord instances."""
from datetime import datetime
from uuid import UUID

from app.models.transaction import TransactionRecord, Direction
from app.models.evidence_image import SourceApp


def parse_extracted_fields(
    raw: dict | list,
    case_id: UUID,
    image_id: UUID,
    source_app: SourceApp,
) -> list[TransactionRecord]:
    """Convert raw extraction dict(s) into TransactionRecord ORM objects."""
    items = raw if isinstance(raw, list) else [raw]
    records: list[TransactionRecord] = []

    for idx, item in enumerate(items):
        if not item or not item.get("amount"):
            continue

        raw_trade_time = item.get("trade_time")
        try:
            if isinstance(raw_trade_time, datetime):
                trade_time = raw_trade_time
            elif isinstance(raw_trade_time, str):
                trade_time = datetime.fromisoformat(raw_trade_time)
            else:
                raise TypeError("trade_time is not str/datetime")
        except (ValueError, KeyError, TypeError):
            trade_time = datetime.now()

        direction_str = item.get("direction", "out")
        direction = Direction.in_ if direction_str == "in" else Direction.out
        try:
            amount = float(item.get("amount", 0))
            confidence = float(item.get("confidence", 0.5))
        except Exception:
            raise

        record = TransactionRecord(
            case_id=case_id,
            evidence_image_id=image_id,
            source_app=source_app,
            trade_time=trade_time,
            amount=amount,
            direction=direction,
            counterparty_name=str(item.get("counterparty_name", "")),
            counterparty_account=str(item.get("counterparty_account", "")),
            self_account_tail_no=str(item.get("self_account_tail_no", "")),
            order_no=str(item.get("order_no", "")),
            remark=str(item.get("remark", "")),
            confidence=confidence,
        )
        records.append(record)

    return records