def _calculate_base_value(self, device_info: Dict) -> float:    """    电商级基础残值计算：融合缓存策略与品牌差异化折旧    适配场景：高并发下的实时估价需求    """    category = device_info.get("category", "手机")    brand = device_info.get("brand", "").lower()    model = device_info.get("model", "").lower()    spec = device_info.get("spec", "").lower()    # 1. 缓存优先：设备基准价缓存12小时（电商接口性能优化关键）    cache_key = f"device:base:price:{category}:{brand}:{model}"    cached_base = self.redis.get(cache_key)    if cached_base:        base_price = float(cached_base)    else:        # 模糊匹配型号（解决电商端型号输入不规范问题）        base_price = self._fuzzy_match_model_price(category, brand, model)        self.redis.setex(cache_key, timedelta(hours=12), base_price)    # 2. 规格溢价（电商接口常见存储分级逻辑）    spec_multiplier = self._get_spec_multiplier(spec)  # 128G→1.2, 256G→1.5    # 3. 品牌差异化折旧（苹果20%/年，安卓30%/年，贴合市场规律）    year_diff = datetime.now().year - device_info.get("purchase_year", 2020)    depreciation = self._get_brand_depreciation(brand, year_diff)    # 4. 行情系数（每日更新，缓存24小时）    market_coeff = self._get_market_coefficient(category, brand)    return round(base_price * spec_multiplier * depreciation * market_coeff, 2)

def quality_check_arbitration(self, estimate_id: str, actual_conditions: Dict) -> Dict:    """    质检差异仲裁：量化价格影响，生成电商端可信报告    """    # 1. 追溯预估数据（Redis缓存预估记录，有效期同报价时效）    cache_key = f"aihuishou:estimate:{estimate_id}"    estimate_data = json.loads(self.redis.get(cache_key).decode())    pre_conditions = estimate_data["condition"]    # 2. 逐项计算差异影响（核心：将定性差异转为定量扣减）    diff_reasons = []    price_diff = 0.0    weight_map = {"外观":0.15, "屏幕":0.2, "电池":0.25, "功能":0.3, "维修史":0.1}    for item, pre_desc in pre_conditions.items():        if item not in actual_conditions:            continue        actual_desc = actual_conditions[item]        # 计算单项得分差异        pre_score = self._get_condition_score(item, pre_desc)        actual_score = self._get_condition_score(item, actual_desc)        score_diff = pre_score - actual_score        # 转化为价格影响（基于基础残值的比例扣减）        item_impact = (score_diff / 10) * estimate_data["base_value"] * weight_map[item]        diff_reasons.append({            "item": item,            "pre_desc": pre_desc,            "actual_desc": actual_desc,            "price_impact": round(item_impact, 2)        })        price_diff += item_impact    # 3. 电商端可接受度判断（差异≤30%则推荐接受）    acceptance = abs(price_diff) / estimate_data["final_price"] <= 0.3    return {        "success": True,        "pre_estimate_price": estimate_data["final_price"],        "actual_price": round(estimate_data["final_price"] - price_diff, 2),        "price_diff": round(price_diff, 2),        "diff_reasons": diff_reasons,        "acceptance": acceptance,        "certificate_id": self._blockchain_deposit(diff_reasons)  # 区块链存证ID    }