"""Rule-based fraud amount assessment.

Classifies each transaction into high / medium / low confidence fraud,
and generates initial reason text.
"""
from app.models.transaction import TransactionRecord
from app.models.assessment import ConfidenceLevel

FRAUD_KEYWORDS = ["投资", "保证金", "手续费", "解冻", "税费", "充值", "提币", "提现"]


def classify_transaction(tx: TransactionRecord) -> tuple[ConfidenceLevel, str, str]:
    """Return (confidence_level, reason, exclude_reason)."""
    if tx.is_transit:
        return (
            ConfidenceLevel.low,
            f"该笔为本人账户间中转（{tx.source_app.value} -> {tx.counterparty_name}），不直接计入被骗损失。",
            "本人账户间互转，仅作为资金路径展示。",
        )

    if tx.direction.value == "in":
        return (
            ConfidenceLevel.low,
            f"该笔为收入方向交易（+¥{float(tx.amount):,.2f}），通常不属于被骗损失。",
            "收入交易不计入损失。",
        )

    remark = tx.remark or ""
    counterparty = tx.counterparty_name or ""
    confidence = tx.confidence

    has_fraud_keyword = any(kw in remark or kw in counterparty for kw in FRAUD_KEYWORDS)

    if confidence >= 0.9 and has_fraud_keyword:
        return (
            ConfidenceLevel.high,
            f"受害人经{tx.source_app.value}向「{counterparty}」转账¥{float(tx.amount):,.2f}，"
            f"备注为「{remark}」，与诈骗常见话术吻合，OCR置信度{confidence:.0%}。",
            "",
        )

    if confidence >= 0.85:
        reason = (
            f"受害人经{tx.source_app.value}向「{counterparty}」转账¥{float(tx.amount):,.2f}。"
        )
        if has_fraud_keyword:
            reason += f"备注「{remark}」含涉诈关键词。"
            return ConfidenceLevel.high, reason, ""
        reason += "建议结合笔录确认是否受诱导操作。"
        return ConfidenceLevel.medium, reason, "如经核实该笔为受害人主动日常消费，应排除。"

    return (
        ConfidenceLevel.medium,
        f"受害人经{tx.source_app.value}向「{counterparty}」转账¥{float(tx.amount):,.2f}，"
        f"OCR置信度较低({confidence:.0%})，需人工复核。",
        "OCR置信度不足，可能存在识别误差。",
    )