"""Transaction data extraction: LLM Vision + persistence."""

from app.models import Transaction
from app.models.database import async_session_maker
from app.schemas.transaction import TransactionExtractItem, TransactionResponse
from app.services.llm import get_llm_provider


async def extract_and_save(
    case_id: int,
    screenshot_id: int,
    image_bytes: bytes,
) -> list[TransactionResponse]:
    """
    Run vision extraction on image and persist transactions to DB.
    Returns list of created transactions; low-confidence items are still saved but flagged.
    """
    provider = get_llm_provider()
    items: list[TransactionExtractItem] = await provider.extract_from_image(image_bytes)
    results: list[TransactionResponse] = []
    async with async_session_maker() as session:
        for it in items:
            t = Transaction(
                case_id=case_id,
                screenshot_id=screenshot_id,
                app_source=it.app_source,
                transaction_type=it.transaction_type,
                amount=it.amount,
                currency=it.currency or "CNY",
                counterparty_name=it.counterparty_name,
                counterparty_account=it.counterparty_account,
                order_number=it.order_number,
                transaction_time=it.transaction_time,
                remark=it.remark,
                confidence=it.confidence if it.confidence in ("high", "medium", "low") else "medium",
                raw_text=None,
            )
            session.add(t)
            await session.flush()
            results.append(TransactionResponse.model_validate(t))
        await session.commit()
    return results