Merge branch 'main' of https://git.1024tool.vip/zfc/guzhi

refactor(valuation): 重构估值计算参数提取逻辑
fix: 修复行业均值S2计算中的除零错误
feat(api): 新增微信指数计算工具和行业数据查询工具
feat(schema): 在估值模型中添加计算结果字段
refactor: 优化动态质押率计算中的月交易额解析
fix: 处理日期解析异常时返回默认值
docs: 更新API文档中的估值计算请求示例

app/api/v1/app_valuations/app_valuations.py

@@ -1,5 +1,8 @@
 from fastapi import APIRouter, Depends, HTTPException, status
-from typing import Optional
+from typing import Optional, List, Dict, Any
+import json
+import asyncio
+import time
 
 from app.controllers.user_valuation import user_valuation_controller
 from app.schemas.valuation import (
@@ -9,89 +12,431 @@ from app.schemas.valuation import (
     UserValuationOut,
     UserValuationDetail
 )
-from app.models.user import AppUser
-
 from app.schemas.base import Success, SuccessExtra
-from app.utils.app_user_jwt import get_current_app_user
+from app.utils.app_user_jwt import get_current_app_user_id, get_current_app_user
+from app.utils.calculation_engine import FinalValueACalculator
+from app.utils.calculation_engine.drp import DynamicPledgeRateCalculator
+from app.utils.calculation_engine.economic_value_b1.sub_formulas.basic_value_b11 import calculate_popularity_score, \
+    calculate_infringement_score, calculate_patent_usage_score
+from app.utils.calculation_engine.economic_value_b1.sub_formulas.traffic_factor_b12 import calculate_search_index_s1
+from app.log.log import logger
+from app.models.esg import ESG
+from app.models.industry import Industry
+from app.models.policy import Policy
+from app.models.user import AppUser
+from app.utils.universal_api_manager import universal_api
+from app.utils.wechat_index_calculator import wechat_index_calculator
 
 app_valuations_router = APIRouter(tags=["用户端估值评估"])
 
 
 @app_valuations_router.post("/", summary="创建估值评估")
-async def create_valuation(
+async def calculate_valuation(
-    data: UserValuationCreate,
+        data: UserValuationCreate,
-    current_user: AppUser = Depends(get_current_app_user)
+        user_id: int = Depends(get_current_app_user_id)
 ):
     """
-    用户创建估值评估申请
+    计算估值评估
+
+    根据用户提交的估值评估数据，调用计算引擎进行经济价值B1计算
+    
+    请求示例JSON (仅包含用户填写部分):
+    {
+        "asset_name": "传统刺绣工艺",
+        "institution": "某文化传承机构", 
+        "industry": "传统手工艺",
+        
+        // 财务状况 (用户填写)
+        "annual_revenue": "500",                    // 近12个月机构营收/万元
+        "rd_investment": "50",                      // 近12个月机构研发投入/万元  
+        "three_year_income": [400, 450, 500],      // 近三年机构收益/万元
+        
+        // 非遗等级与技术 (用户填写)
+        "inheritor_level": "国家级传承人",          // 非遗传承人等级
+        "inheritor_ages": [45, 60, 75],            // 传承人年龄列表
+        "heritage_level": "国家级",                 // 非遗等级
+        "patent_application_no": "CN202310123456.7", // 专利申请号
+        "patent_remaining_years": "15",             // 专利剩余年限
+        "historical_evidence": {                   // 历史证明证据及数量
+            "历史文献": 3, 
+            "考古发现": 2, 
+            "传承谱系": 5
+        },
+        "pattern_images": ["demo.jpg"], // 非遗纹样图片
+        
+        // 非遗应用与推广 (用户填写)
+        "application_maturity": "成熟应用",         // 应用成熟度
+        "application_coverage": "全国覆盖",         // 应用覆盖范围
+        "cooperation_depth": "0.5",               // 跨界合作深度
+        "offline_activities": "12",               // 近12个月线下宣讲活动次数
+        "online_accounts": [                      // 线上宣传账号信息
+            {"platform": "抖音", "account": "传统刺绣大师"},
+            {"platform": "微博", "account": "非遗传承人"}
+        ],
+        
+        // 市场信息 (用户填写)
+        "sales_volume": "1000",                   // 近12个月销售量
+        "link_views": "5000",                     // 近12个月链接浏览量
+        "circulation": "限量",                    // 发行量
+        "last_market_activity": "2024-01-15",     // 最近一次市场活动时间
+        "price_fluctuation": [95.0, 105.0],       // 近30天价格波动区间
+        "manual_bids": [48000.0, 50000.0, 52000.0], // 手动收集的竞价列表
+        
+        // 政策相关 (用户填写)
+        "funding_status": "国家级资助",           // 资金支持情况
+        "implementation_stage": "成熟应用"         // 实施阶段
+    }
+    
+    API获取参数 (系统自动获取，无需用户填写):
+    - 搜索指数: 百度、微信、微博搜索指数
+    - 社交媒体数据: 点赞数、评论数、转发数、粉丝数
+    - 交易数据: 近3个月加权平均价格
+    - 热度数据: 近7日日均浏览量、收藏数
+    - ESG评分: 根据行业自动匹配
+    - 行业系数: 根据行业ROE计算
+    - 政策匹配度: 根据行业自动匹配
+    - 专利验证: 通过API验证专利有效性
+    - 侵权记录: 通过API查询侵权诉讼历史
     """
     try:
+        start_ts = time.monotonic()
+        logger.info("valuation.calc_start user_id={} asset_name={} industry={}", user_id, getattr(data, 'asset_name', None), getattr(data, 'industry', None))
+
+        # 根据行业查询 ESG 基准分（优先用行业名称匹配，如用的是行业代码就把 name 改成 code）
+        esg_obj = None
+        industry_obj = None
+        policy_obj = None
+        
+        try:
+            esg_obj = await asyncio.wait_for(ESG.filter(name=data.industry).first(), timeout=2.0)
+        except Exception as e:
+            logger.warning("valuation.esg_fetch_timeout industry={} err={}", data.industry, repr(e))
+        esg_score = float(getattr(esg_obj, 'number', 0.0) or 0.0)
+
+        # 根据行业查询 行业修正系数与ROE
+        try:
+            industry_obj = await asyncio.wait_for(Industry.filter(name=data.industry).first(), timeout=2.0)
+        except Exception as e:
+            logger.warning("valuation.industry_fetch_timeout industry={} err={}", data.industry, repr(e))
+        fix_num_score = getattr(industry_obj, 'fix_num', 0.0) or 0.0
+
+        # 根据行业查询 政策匹配度
+        try:
+            policy_obj = await asyncio.wait_for(Policy.filter(name=data.industry).first(), timeout=2.0)
+        except Exception as e:
+            logger.warning("valuation.policy_fetch_timeout industry={} err={}", data.industry, repr(e))
+        policy_match_score = getattr(policy_obj, 'score', 0.0) or 0.0
+        # 提取 经济价值B1 计算参数
+        input_data_by_b1 = await _extract_calculation_params_b1(data)
+        # ESG关联价值 ESG分 (0-10分)
+        input_data_by_b1["esg_score"] = esg_score
+        # 行业修正系数I
+        input_data_by_b1["industry_coefficient"] = fix_num_score
+        # 政策匹配度
+        input_data_by_b1["policy_match_score"] = policy_match_score
+
+        # 获取专利信息 TODO 参数
+
+        try:
+            patent_data = universal_api.query_patent_info("未找到 企业名称、企业统代、企业注册号")
+            patent_dict = patent_data if isinstance(patent_data, dict) else {}
+            inner_data = patent_dict.get("data", {}) if isinstance(patent_dict.get("data", {}), dict) else {}
+            data_list = inner_data.get("dataList", [])
+            data_list = data_list if isinstance(data_list, list) else []
+            # 验证 专利剩余年限
+            # TODO 无法验证 专利剩余保护期>10年(10分)，5-10年(7分)，<5年(3分)；
+
+            # 发展潜力D相关参数 专利数量
+            # 查询匹配申请号的记录集合
+            matched = [item for item in data_list if isinstance(item, dict) and item.get("SQH") == getattr(data, 'patent_application_no', None)]
+            if matched:
+                patent_count = calculate_patent_usage_score(len(matched))
+                input_data_by_b1["patent_count"] = float(patent_count)
+            else:
+                input_data_by_b1["patent_count"] = 0.0
+                input_data_by_b1["patent_score"] = 0
+        except Exception as e:
+            logger.warning("valuation.patent_api_error err={}", repr(e))
+            input_data_by_b1["patent_count"] = 0.0
+
+        #  提取 文化价值B2 计算参数
+        input_data_by_b2 = await _extract_calculation_params_b2(data)
+        # 提取 风险调整系数B3 计算参数
+        input_data_by_b3 = await _extract_calculation_params_b3(data)
+        # 提取 市场估值C 参数
+        input_data_by_c = await _extract_calculation_params_c(data)
+
+
+        input_data = {
+            # 模型估值B 相关参数
+            "model_data": {
+                # 经济价值B1 参数
+                "economic_data": input_data_by_b1,
+                # 文化价值B2 参数
+                "cultural_data": input_data_by_b2,
+                # 风险调整参数 B3
+                "risky_data": input_data_by_b3,
+            },
+            # 市场估值C 参数
+            "market_data": input_data_by_c,
+        }
+
+        calculator = FinalValueACalculator()
+        # 计算最终估值A（统一计算）
+        calculation_result = calculator.calculate_complete_final_value_a(input_data)
+
+        # 计算动态质押
+        drp_c = DynamicPledgeRateCalculator()
+        '''
+        monthly_amount (float): 月交易额（万元）
+        heritage_level (str): 非遗等级
+        '''
+        # 解析月交易额字符串为数值
+        monthly_amount = drp_c.parse_monthly_transaction_amount(data.monthly_transaction_amount or "")
+        drp_result = drp_c.calculate_dynamic_pledge_rate(monthly_amount, data.heritage_asset_level)
+
+        # 结构化日志：关键分值
+        try:
+            duration_ms = int((time.monotonic() - start_ts) * 1000)
+            logger.info(
+                "valuation.calc_done user_id={} duration_ms={} model_value_b={} market_value_c={} final_value_ab={}",
+                user_id,
+                duration_ms,
+                calculation_result.get('model_value_b'),
+                calculation_result.get('market_value_c'),
+                calculation_result.get('final_value_ab'),
+            )
+        except Exception:
+            pass
+        # 创建估值评估记录
         result = await user_valuation_controller.create_valuation(
-            user_id=current_user.id,
+            user_id=user_id,
-            data=data
+            data=data,
+            calculation_result=calculation_result,
+            calculation_input={
+                'model_data': {
+                    'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()),
+                    'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()),
+                    'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()),
+                },
+                'market_data': list(input_data.get('market_data', {}).keys()),
+            },
+            drp_result=drp_result
         )
-        # 使用model_dump_json()来正确序列化datetime，然后解析为dict
+
-        import json
+        # 组装返回
         result_dict = json.loads(result.model_dump_json())
-        # 开始计算 估值 信息
+        #         "calculation_result": {
-        # 1 # 经济价值B1模块: EconomicValueB1Calculator | BasicValueB11Calculator | TrafficFactorB12Calculator | PolicyMultiplierB13Calculator
+        #             "model_value_b": 660.1534497474814,
-        # 1.1 EconomicValueB1Calculator
+        #             "market_value_c": 8800.0,
-    #     input_data = {
+        #             "final_value_ab": 3102.107414823237
-    #         # 基础价值B11相关参数
+        #         }
-    #         'three_year_income': data.three_year_income,
+        result_dict['calculation_result'] = calculation_result
-    #         'patent_score': data.pa,  # 专利分
-    #         'popularity_score': data.popularity_score,  # 普及地域分值
-    #         'infringement_score': data.infringement_score,  # 侵权分
-    #         'innovation_ratio': data.innovation_ratio,
-    #         'esg_score':data.esg_score,
-    #         'industry_coefficient':data.industry_coefficient,
 
-    #         # 流量因子B12相关参数
+        result_dict['calculation_input'] = {
-    #         'search_index_s1': 4500.0,
+            'model_data': {
-    #         'industry_average_s2': 5000.0,
+                'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()),
-    #         # 'social_media_spread_s3': social_media_spread_s3,
+                'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()),
-    #         'likes': 4, # 点赞
+                'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()),
-    #         'comments': 5, # 评论
+            },
-    #         'shares': 6, # 转发
+            'market_data': list(input_data.get('market_data', {}).keys()),
-    #         'followers': 7, # 粉丝数
+        }
 
-    #         'click_count': 1000,# 点击量
+        return Success(data=result_dict, msg="估值计算完成")
-    #         'view_count': 100, # 内容浏览量
 
-    #         # 政策乘数B13相关参数
-    #         'policy_match_score': 10.0,  # 政策匹配度
-    #         'implementation_stage': 10.0,  # 实施阶段评分
-    #         'funding_support': 10.0  # 资金支持度
-    # }
-        # 1.2 BasicValueB11Calculator
-        # 1.3 TrafficFactorB12Calculator
-        # 1.4 PolicyMultiplierB13Calculator
-
-        # 2 # 文化价值B2模块: CulturalValueB2Calculator | LivingHeritageB21Calculator | PatternGeneB22Calculator
-        # 2.1 CulturalValueB2Calculator
-        # 2.2 LivingHeritageB21Calculator
-        # 2.3 PatternGeneB22Calculator
-
-        # 3 # 风险调整系数B3模块: RiskAdjustmentB3Calculator
-        # 3.1 RiskAdjustmentB3Calculator
-
-        # 4 # 市场估值C模块: MarketValueCCalculator | MarketBiddingC1Calculator | HeatCoefficientC2Calculator | ScarcityMultiplierC3Calculator | TemporalDecayC4Calculator
-        # 4.1 MarketValueCCalculator
-        # 4.2 MarketBiddingC1Calculator
-        # 4.3 HeatCoefficientC2Calculator
-        # 4.4 ScarcityMultiplierC3Calculator
-        # 4.5 TemporalDecayC4Calculator
-
-        # 5 # 最终估值A模块: FinalValueACalculator
-        # 5.1 FinalValueACalculator
-        return Success(data=result_dict, msg="估值评估申请提交成功")
     except Exception as e:
-        raise HTTPException(
+        import traceback
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+        print(traceback.format_exc())
-            detail=f"创建估值评估失败: {str(e)}"
+        logger.error("valuation.calc_failed user_id={} err={}", user_id, repr(e))
-        )
+        raise HTTPException(status_code=400, detail=f"计算失败: {str(e)}")
 
 
+async def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]:
+    """
+    从用户提交的数据中提取计算所需的参数
+    
+    Args:
+        data: 用户提交的估值评估数据
+        
+    Returns:
+        Dict: 计算所需的参数字典
+    """
+    # 基础价值B11相关参数
+    # 财务价值所需数据 从近三年收益计算
+    three_year_income = data.three_year_income or [0, 0, 0]
+
+    # 法律强度L相关参数
+    # 普及地域分值 默认 7分
+    popularity_score = calculate_popularity_score(data.application_coverage)
+
+    # 侵权分 默认 6 TODO  需要使用第三方API 无侵权记录(10分)，历史侵权已解决(6分)，现存纠纷(2分)
+    infringement_score = calculate_infringement_score("无侵权信息")
+    infringement_score = 0
+
+    # 创新投入比 = (研发费用/营收) * 100
+    try:
+        rd_investment = float(data.rd_investment or 0)
+        annual_revenue = float(data.annual_revenue or 1)  # 避免除零
+        innovation_ratio = (rd_investment / annual_revenue) * 100 if annual_revenue > 0 else 0
+    except (ValueError, TypeError):
+        innovation_ratio = 0.0
+
+
+    # 流量因子B12相关参数
+    # 近30天搜索指数S1 - 从社交媒体数据计算 TODO  需要使用第三方API
+    baidu_index = 0
+    
+    # 获取微信指数并计算近30天平均值
+    try:
+        1/0
+        wechat_index_response = universal_api.wx_index(data.asset_name)
+        wechat_index = wechat_index_calculator.process_wechat_index_response(wechat_index_response)
+        logger.info(f"资产 '{data.asset_name}' 的微信指数近30天平均值: {wechat_index}")
+    except Exception as e:
+        logger.error(f"获取微信指数失败: {e}")
+        wechat_index = 0
+    
+    weibo_index = 0
+    search_index_s1 = calculate_search_index_s1(baidu_index,wechat_index,weibo_index) # 默认值，实际应从API获取
+    
+    # 行业均值S2 - 从数据库查询行业数据计算
+    from app.utils.industry_calculator import calculate_industry_average_s2
+    industry_average_s2 = await calculate_industry_average_s2(data.industry)
+    # 社交媒体传播度S3 - TODO  需要使用第三方API,click_count view_count 未找到对应参数
+    # likes: 点赞数(API获取)
+    # comments: 评论数(API获取)
+    # shares: 转发数(API获取)
+    # followers: 粉丝数
+    # click_count: 商品链接点击量(用户填写) sales_volume 使用 sales_volume 销售量
+    # view_count: 内容浏览量(用户填写) link_views
+
+    # 政策乘数B13相关参数
+    # 政策契合度评分P - 根据行业和资助情况计算
+    # 实施阶段 - 需要转换为对应的评分
+    implementation_stage_str = data.application_maturity or "成熟应用"
+    # 资金支持 - 需要转换为对应的评分
+    funding_support_str = data.funding_status or "无资助"
+    
+    # 使用PolicyMultiplierB13Calculator来计算评分
+    from app.utils.calculation_engine.economic_value_b1.sub_formulas.policy_multiplier_b13 import PolicyMultiplierB13Calculator
+    policy_calculator = PolicyMultiplierB13Calculator()
+    implementation_stage = policy_calculator.calculate_implementation_stage_score(implementation_stage_str)
+    funding_support = policy_calculator.calculate_funding_support_score(funding_support_str)
+
+    return {
+        # 基础价值B11相关参数
+        'three_year_income': three_year_income,
+        'popularity_score': popularity_score,
+        'infringement_score': infringement_score,
+        'innovation_ratio': innovation_ratio,
+
+        # 流量因子B12相关参数
+        'search_index_s1': search_index_s1,
+        'industry_average_s2': industry_average_s2,
+        'social_media_spread_s3': 0.0,
+        # 这些社交数据暂未来源，置为0，后续接入API再填充
+        'likes': 0,
+        'comments': 0,
+        'shares': 0,
+        # followers 非当前计算用键，先移除避免干扰
+
+        # click_count 与 view_count 目前未参与计算，先移除
+
+        # 政策乘数B13相关参数
+        'implementation_stage': implementation_stage,
+        'funding_support':funding_support
+    }
+
+# 获取 文化价值B2 相关参数
+async def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, Any]:
+    """
+    argrg:
+        data: 用户提交的估值评估数据
+
+    retus:
+        Dict: 计算所需的参数字典
+    """
+    # 导入计算器来转换传承人等级
+    from app.utils.calculation_engine.cultural_value_b2.sub_formulas.living_heritage_b21 import LivingHeritageB21Calculator
+    
+    # 活态传承系数B21 县官参数
+    living_heritage_calculator = LivingHeritageB21Calculator()
+    inheritor_level = data.inheritor_level or "市级传承人"  # 设置默认值
+    inheritor_level_coefficient = living_heritage_calculator.calculate_inheritor_level_coefficient(inheritor_level)
+    
+    offline_sessions = int(data.offline_activities) #线下传习次数
+    # 以下调用API douyin\bilibili\kuaishou
+    douyin_views = 0
+    kuaishou_views= 0
+    bilibili_views= 0
+    # 跨界合作深度 品牌联名0.3，科技载体0.5，国家外交礼品1.0
+    cross_border_depth = float(data.cooperation_depth)
+
+    # 纹样基因值B22相关参数
+
+    # 以下三项需由后续模型/服务计算；此处提供默认可计算占位
+    historical_inheritance = 0.8
+    structure_complexity = 0.75
+    normalized_entropy = 0.85
+    return {
+        "inheritor_level_coefficient": inheritor_level_coefficient,
+        "offline_sessions": offline_sessions,
+        "douyin_views": douyin_views,
+        "kuaishou_views": kuaishou_views,
+        "bilibili_views": bilibili_views,
+        "cross_border_depth": cross_border_depth,
+        "historical_inheritance": historical_inheritance,
+        "structure_complexity": structure_complexity,
+        "normalized_entropy": normalized_entropy,
+    }
+
+# 获取 文化价值B2 相关参数
+async def _extract_calculation_params_b3(data: UserValuationCreate) -> Dict[str, Any]:
+    # 过去30天最高价格 过去30天最低价格 TODO 需要根据字样进行切分获取最高价和最低价 转换成 float 类型
+    highest_price,lowest_price= data.price_fluctuation
+    lawsuit_status = "无诉讼"  # 诉讼状态 TODO (API获取)
+    inheritor_ages = data.inheritor_age_count # [45, 60, 75]  # 传承人年龄列表
+    return {
+        "highest_price": highest_price,
+        "lowest_price": lowest_price,
+        "lawsuit_status": lawsuit_status,
+        "inheritor_ages": inheritor_ages,
+    }
+
+
+# 获取 市场估值C 相关参数
+async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str, Any]:
+    # 市场竞价C1 TODO 暂无
+    # transaction_data: 交易数据字典(API获取)
+    # manual_bids: 手动收集的竞价列表(用户填写)
+    # expert_valuations: 专家估值列表(系统配置)
+    transaction_data: Dict = None
+    manual_bids: List[float] = None
+    expert_valuations: List[float] = None
+    # 浏览热度分 TODO 需要先确定平台信息
+    daily_browse_volume = 500.0 # 近7日日均浏览量(默认占位)
+    collection_count = 50 # 收藏数(默认占位)
+    # 稀缺性乘数C3 发行量
+    circulation = data.circulation or '限量'
+
+    # 时效性衰减C4 参数  用户选择距离最近一次市场活动（交易、报价、评估）的相距时间
+    recent_market_activity = data.last_market_activity
+    # 如果为空、None或"0"，设置默认值
+    if not recent_market_activity or recent_market_activity == "0":
+        recent_market_activity = '2024-01-15'
+    return {
+        # 计算市场竞价C1
+        # C1 的实现接受 transaction_data={'weighted_average_price': x}
+        "weighted_average_price": transaction_data,
+        "manual_bids": manual_bids,   # 手动收集的竞价列表 (用户填写)
+        "expert_valuations": expert_valuations, # 专家估值列表 (系统配置)
+        # 计算热度系数C2
+        "daily_browse_volume": daily_browse_volume, # 近7日日均浏览量 (API获取)
+        "collection_count": collection_count, # 收藏数
+        "issuance_level": circulation, # 默认 限量发行 计算稀缺性乘数C3
+        "recent_market_activity": recent_market_activity, # 默认 '近一月' 计算市场估值C
+    }
+
 @app_valuations_router.get("/", summary="获取我的估值评估列表")
 async def get_my_valuations(
     query: UserValuationQuery = Depends(),

app/api/v1/app_valuations/wechat_index.txt

@@ -0,0 +1,261 @@
+{
+    'category': [
+        {
+            'type': 0,
+            'word': '全部'
+        },
+        {
+            'type': 7,
+            'word': '视频号'
+        },
+        {
+            'type': 2,
+            'word': '文章'
+        },
+        {
+            'type': 1,
+            'word': '公众号'
+        },
+        {
+            'type': 262208,
+            'word': '小程序'
+        },
+        {
+            'extra_kvs': [
+                {
+                    'key': 'modelName',
+                    'value': 'hunyuan-t1-turbos'
+                },
+                {
+                    'key': 'modelType',
+                    'value': 't1'
+                },
+                {
+                    'key': 'fastModelType',
+                    'value': 'fast'
+                }
+            ],
+            'type': 53,
+            'word': 'AI搜索'
+        },
+        {
+            'type': 9,
+            'word': '直播'
+        },
+        {
+            'type': 1024,
+            'word': '读书'
+        },
+        {
+            'type': 512,
+            'word': '听一听'
+        },
+        {
+            'type': 384,
+            'word': '表情'
+        },
+        {
+            'type': 16777728,
+            'word': '百科'
+        },
+        {
+            'type': 16384,
+            'word': '新闻'
+        },
+        {
+            'selected': 1,
+            'type': 8192,
+            'word': '微信指数'
+        },
+        {
+            'type': 33562630,
+            'word': '划线'
+        },
+        {
+            'type': 8,
+            'word': '朋友圈'
+        }
+    ],
+    'continueFlag': 0,
+    'cookies': '{"box_offset":0,"businessType":8192,"cookies_buffer":"UisIYhABGIBAIgzotYTkuqflkI3np7BQAYIBBRAAogEAsgECGACaAwRCAHIA","doc_offset":0,"dup_bf":"","isHomepage":0,"page_cnt":1,"query":"资产名称","scene":98}\n',
+    'data': [
+        {
+            'boxID': '0x40000-15048-',
+            'boxPos': 1,
+            'boxPosMerge': 1,
+            'count': 1,
+            'items': [
+                {
+                    'docID': '1-7123206500956315942',
+                    'itemInfo': {
+                        'data': [
+                            {
+                                'index': '113',
+                                'timestamp': 1757433600
+                            },
+                            {
+                                'index': '51',
+                                'timestamp': 1757520000
+                            },
+                            {
+                                'index': '112',
+                                'timestamp': 1757606400
+                            },
+                            {
+                                'index': '26',
+                                'timestamp': 1757692800
+                            },
+                            {
+                                'index': '24',
+                                'timestamp': 1757779200
+                            },
+                            {
+                                'index': '118',
+                                'timestamp': 1757865600
+                            },
+                            {
+                                'index': '46',
+                                'timestamp': 1757952000
+                            },
+                            {
+                                'index': '90',
+                                'timestamp': 1758038400
+                            },
+                            {
+                                'index': '200',
+                                'timestamp': 1758124800
+                            },
+                            {
+                                'index': '70',
+                                'timestamp': 1758211200
+                            },
+                            {
+                                'index': '23',
+                                'timestamp': 1758297600
+                            },
+                            {
+                                'index': '1',
+                                'timestamp': 1758384000
+                            },
+                            {
+                                'index': '44',
+                                'timestamp': 1758470400
+                            },
+                            {
+                                'index': '93',
+                                'timestamp': 1758556800
+                            },
+                            {
+                                'index': '91',
+                                'timestamp': 1758643200
+                            },
+                            {
+                                'index': '6',
+                                'timestamp': 1758729600
+                            },
+                            {
+                                'index': '46',
+                                'timestamp': 1758816000
+                            },
+                            {
+                                'index': '1',
+                                'timestamp': 1758902400
+                            },
+                            {
+                                'index': '66',
+                                'timestamp': 1758988800
+                            },
+                            {
+                                'index': '45',
+                                'timestamp': 1759075200
+                            },
+                            {
+                                'index': '23',
+                                'timestamp': 1759161600
+                            },
+                            {
+                                'index': '22',
+                                'timestamp': 1759248000
+                            },
+                            {
+                                'index': '0',
+                                'timestamp': 1759334400
+                            },
+                            {
+                                'index': '0',
+                                'timestamp': 1759420800
+                            },
+                            {
+                                'index': '22',
+                                'timestamp': 1759507200
+                            },
+                            {
+                                'index': '22',
+                                'timestamp': 1759593600
+                            },
+                            {
+                                'index': '23',
+                                'timestamp': 1759680000
+                            },
+                            {
+                                'index': '1',
+                                'timestamp': 1759766400
+                            },
+                            {
+                                'index': '0',
+                                'timestamp': 1759852800
+                            },
+                            {
+                                'index': '24',
+                                'timestamp': 1759939200
+                            }
+                        ],
+                        'title': '资产名称 - 微信指数',
+                        'type': 1058
+                    },
+                    'jumpInfo': {
+                        'jumpType': 2,
+                        'reportId': 'chart:chart:317451',
+                        'userName': 'gh_935b85261f35@app',
+                        'weappUrl': '/page/detail/detail?calculate_word=资产名称'
+                    },
+                    'source': {
+                        'iconUrl': 'http://mmbiz.qpic.cn/mmbiz_png/uic3vZ5pI29sdd0tUo5t4pxmJMsMO9iaxM8EOxTX1VUAWjQibib0juc81kMkUgtB9IibIg58TZocULicPJ7lichq8E1VQ/640?wx_fmt=png&wxfrom=200',
+                        'title': '微信指数'
+                    },
+                    'title': ''
+                }
+            ],
+            'real_type': 262144,
+            'subType': 15048,
+            'type': 52
+        }
+    ],
+    'direction': 2,
+    'enableQuestionClosely': False,
+    'experiment': [
+        {
+            'key': 's1s_all_prefetch_next_page',
+            'value': '2'
+        },
+        {
+            'key': 'mmsearch_exp_financial_style',
+            'value': '2'
+        }
+    ],
+    'isAutoPlayVideo': 1,
+    'isDivide': 0,
+    'isHomePage': 0,
+    'lang': 'zh_CN',
+    'nomoreText': '没有更多的搜索结果',
+    'offset': 20,
+    'pageNumber': 1,
+    'query': '资产名称',
+    'resultType': 0,
+    'ret': 0,
+    'searchID': '1448000677067408154',
+    'timeStamp': 1760081917,
+    'code': 0,
+    'cost_money': 0.5,
+    'remain_money': 28.5
+}

app/api/v1/calculation/calcuation.py

@@ -191,7 +191,9 @@ async def calculate_valuation(
         monthly_amount (float): 月交易额（万元）
         heritage_level (str): 非遗等级
         '''
-        drp_result = drp_c.calculate_dynamic_pledge_rate(float(data.monthly_transaction_amount),data.heritage_asset_level)
+        # 解析月交易额字符串为数值
+        monthly_amount = drp_c.parse_monthly_transaction_amount(data.monthly_transaction_amount or "")
+        drp_result = drp_c.calculate_dynamic_pledge_rate(monthly_amount, data.heritage_asset_level)
 
         # 结构化日志：关键分值
         try:
@@ -209,7 +211,17 @@ async def calculate_valuation(
         # 创建估值评估记录
         result = await user_valuation_controller.create_valuation(
             user_id=user_id,
-            data=data
+            data=data,
+            calculation_result=calculation_result,
+            calculation_input={
+                'model_data': {
+                    'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()),
+                    'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()),
+                    'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()),
+                },
+                'market_data': list(input_data.get('market_data', {}).keys()),
+            },
+            drp_result=drp_result
         )
 
         # 组装返回
@@ -319,8 +331,14 @@ async def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str,
     retus:
         Dict: 计算所需的参数字典
     """
+    # 导入计算器来转换传承人等级
+    from app.utils.calculation_engine.cultural_value_b2.sub_formulas.living_heritage_b21 import LivingHeritageB21Calculator
+    
     # 活态传承系数B21 县官参数
-    inheritor_level_coefficient = data.inheritor_level # 传承人等级
+    living_heritage_calculator = LivingHeritageB21Calculator()
+    inheritor_level = data.inheritor_level or "市级传承人"  # 设置默认值
+    inheritor_level_coefficient = living_heritage_calculator.calculate_inheritor_level_coefficient(inheritor_level)
+    
     offline_sessions = int(data.offline_activities) #线下传习次数
     # 以下调用API douyin\bilibili\kuaishou
     douyin_views = 0
@@ -377,7 +395,10 @@ async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str,
     circulation = data.circulation or '限量'
 
     # 时效性衰减C4 参数  用户选择距离最近一次市场活动（交易、报价、评估）的相距时间
-    recent_market_activity = data.last_market_activity or '2024-01-15'
+    recent_market_activity = data.last_market_activity
+    # 如果为空、None或"0"，设置默认值
+    if not recent_market_activity or recent_market_activity == "0":
+        recent_market_activity = '2024-01-15'
     return {
         # 计算市场竞价C1
         # C1 的实现接受 transaction_data={'weighted_average_price': x}

app/controllers/user_valuation.py

@@ -18,12 +18,25 @@ class UserValuationController:
     def __init__(self):
         self.model = ValuationAssessment
     
-    async def create_valuation(self, user_id: int, data: UserValuationCreate) -> UserValuationDetail:
+    async def create_valuation(self, user_id: int, data: UserValuationCreate, calculation_result: dict = None, calculation_input: dict = None, drp_result: float = None) -> UserValuationDetail:
         """用户创建估值评估"""
         valuation_data = data.model_dump()
         valuation_data['user_id'] = user_id
         valuation_data['status'] = 'pending'  # 默认状态为待审核
         
+        # 添加计算结果到数据库
+        if calculation_result:
+            valuation_data['model_value_b'] = calculation_result.get('model_value_b')
+            valuation_data['market_value_c'] = calculation_result.get('market_value_c')
+            valuation_data['final_value_ab'] = calculation_result.get('final_value_ab')
+            valuation_data['calculation_result'] = calculation_result
+        
+        if calculation_input:
+            valuation_data['calculation_input'] = calculation_input
+            
+        if drp_result is not None:
+            valuation_data['dynamic_pledge_rate'] = drp_result
+        
         valuation = await self.model.create(**valuation_data)
         return await self._to_user_detail(valuation)
     
@@ -141,6 +154,13 @@ class UserValuationController:
             legal_risk=valuation.legal_risk,
             base_pledge_rate=valuation.base_pledge_rate,
             flow_correction=valuation.flow_correction,
+            # 添加计算结果字段
+            model_value_b=valuation.model_value_b,
+            market_value_c=valuation.market_value_c,
+            final_value_ab=valuation.final_value_ab,
+            dynamic_pledge_rate=valuation.dynamic_pledge_rate,
+            calculation_result=valuation.calculation_result,
+            calculation_input=valuation.calculation_input,
             status=valuation.status,
             admin_notes=valuation.admin_notes,
             created_at=valuation.created_at,

app/models/valuation.py

@@ -68,6 +68,14 @@ class ValuationAssessment(Model):
     base_pledge_rate = fields.CharField(max_length=50, null=True, description="基础质押率")
     flow_correction = fields.CharField(max_length=50, null=True, description="流量修正系数")
     
+    # 计算结果字段
+    model_value_b = fields.FloatField(null=True, description="模型估值B（万元）")
+    market_value_c = fields.FloatField(null=True, description="市场估值C（万元）")
+    final_value_ab = fields.FloatField(null=True, description="最终估值AB（万元）")
+    dynamic_pledge_rate = fields.FloatField(null=True, description="动态质押率")
+    calculation_result = fields.JSONField(null=True, description="完整计算结果JSON")
+    calculation_input = fields.JSONField(null=True, description="计算输入参数JSON")
+    
     # 系统字段
     user = fields.ForeignKeyField("models.AppUser", related_name="valuations", description="提交用户")
     status = fields.CharField(max_length=20, default="pending", description="评估状态: pending(待审核), approved(已通过), rejected(已拒绝)")

app/schemas/valuation.py

@@ -66,6 +66,14 @@ class ValuationAssessmentBase(BaseModel):
     base_pledge_rate: Optional[str] = Field(None, description="基础质押率")
     flow_correction: Optional[str] = Field(None, description="流量修正系数")
     
+    # 计算结果字段
+    model_value_b: Optional[float] = Field(None, description="模型估值B（万元）")
+    market_value_c: Optional[float] = Field(None, description="市场估值C（万元）")
+    final_value_ab: Optional[float] = Field(None, description="最终估值AB（万元）")
+    dynamic_pledge_rate: Optional[float] = Field(None, description="动态质押率")
+    calculation_result: Optional[Dict[str, Any]] = Field(None, description="完整计算结果JSON")
+    calculation_input: Optional[Dict[str, Any]] = Field(None, description="计算输入参数JSON")
+
 
 class ValuationAssessmentCreate(ValuationAssessmentBase):
     """创建估值评估模型"""

app/settings/config.py

@@ -18,9 +18,9 @@ class Settings(BaseSettings):
     DEBUG: bool = True
     
     # 服务器配置
-    SERVER_HOST: str = "127.0.0.1"
+    SERVER_HOST: str = "124.222.245.240"
     SERVER_PORT: int = 9999
-    BASE_URL: str = f"http://{SERVER_HOST}:{SERVER_PORT}"
+    BASE_URL: str = f"http://{SERVER_HOST}:8080"
 
     PROJECT_ROOT: str = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir))
     BASE_DIR: str = os.path.abspath(os.path.join(PROJECT_ROOT, os.pardir))

app/utils/api_config.py

@@ -127,15 +127,6 @@ class APIConfig:
                         "description": "该接口用于获取指定B站视频的详细信息，包括视频地址、描述文案、作者信息、发布时间、播放量、点赞数、评论数与分享数等",
                         "required_params": ["token", "bvid"],
                         "optional_params": []
-                    },
-                    "jizhiliao_index_search": {
-                        "path": "/fbmain/monitor/v3/web_search",
-                        "method": "POST",
-                        "description": "极致聊指数搜索",
-                        "api_key": os.getenv("JIZHILIAO_API_KEY", "JZL089ef0b7d0315d96"),
-                        "verifycode": os.getenv("JIZHILIAO_VERIFYCODE", ""),
-                        "required_params": ["keyword", "mode", "BusinessType", "sub_search_type"],
-                        "optional_params": ["key", "verifycode"]
                     }
                 }
             },
@@ -148,9 +139,11 @@ class APIConfig:
                     "web_search": {
                         "path": "/fbmain/monitor/v3/web_search",
                         "method": "POST",
-                        "description": "获取微信指数",
+                        "description": "极致聊指数搜索",
-                        "required_params": ["keyword", "key"],
+                        "api_key": os.getenv("JIZHILIAO_API_KEY", "JZL089ef0b7d0315d96"),
-                        "optional_params": []
+                        "verifycode": os.getenv("JIZHILIAO_VERIFYCODE", ""),
+                        "required_params": ["keyword", "mode", "BusinessType", "sub_search_type"],
+                        "optional_params": ["key", "verifycode"]
                     }
                 }
             },

app/utils/calculation_engine/drp/sub_formulas/dynamic_pledge_rate.py

@@ -66,6 +66,47 @@ class DynamicPledgeRateCalculator:
         else:
             return 0.0
 
+    def parse_monthly_transaction_amount(self, monthly_transaction_str: str) -> float:
+        """
+        解析月交易额字符串，转换为数值（万元）
+
+        参数:
+            monthly_transaction_str (str): 月交易额字符串，如"月交易额<100万元"、"100-500万元"等
+
+        返回:
+            float: 月交易额数值（万元）
+        """
+        if not monthly_transaction_str:
+            return 0.0
+        
+        # 清理字符串，移除空格和常见前缀
+        clean_str = monthly_transaction_str.strip().replace("月交易额", "").replace("万元", "")
+        
+        # 处理不同的格式
+        if "<100" in clean_str or "小于100" in clean_str:
+            return 50.0  # 取中间值
+        elif "100-500" in clean_str or "100万-500万" in clean_str:
+            return 300.0  # 取中间值
+        elif ">500" in clean_str or "大于500" in clean_str or "≥500" in clean_str:
+            return 600.0  # 取一个合理值
+        elif "500-1000" in clean_str:
+            return 750.0  # 取中间值
+        elif ">1000" in clean_str or "大于1000" in clean_str:
+            return 1200.0  # 取一个合理值
+        else:
+            # 尝试提取数字
+            import re
+            numbers = re.findall(r'\d+', clean_str)
+            if numbers:
+                # 如果有多个数字，取平均值
+                if len(numbers) >= 2:
+                    return (float(numbers[0]) + float(numbers[1])) / 2
+                else:
+                    return float(numbers[0])
+            else:
+                # 默认值
+                return 50.0
+
     def get_monthly_transaction_score(self, monthly_amount: float) -> float:
         """
         根据用户月交易额区间匹配评分。

app/utils/calculation_engine/economic_value_b1/sub_formulas/traffic_factor_b12.py

@@ -28,10 +28,10 @@ class TrafficFactorB12Calculator:
             float: 流量因子B12
         """
         # 避免除零和对数计算错误
-        if industry_average_s2 <= 0:
+        if industry_average_s2 == 0:
             raise ValueError("行业均值S2必须大于0")
         
-        if search_index_s1 <= 0:
+        if search_index_s1 == 0:
             # 如果搜索指数为0或负数，使用最小值避免对数计算错误
             search_index_s1 = 1.0
         

app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py

@@ -45,6 +45,11 @@ class TemporalDecayC4Calculator:
 
         # 处理输入日期
         if isinstance(target_date, str):
+            # 如果是数字字符串"0"或空字符串，使用默认日期
+            if target_date == "0" or target_date.strip() == "":
+                # 默认为一年前，返回"其他"
+                return "其他"
+            
             # 尝试不同的日期格式
             formats = ['%Y-%m-%d', '%Y/%m/%d', '%Y%m%d']
             date_obj = None
@@ -55,9 +60,15 @@ class TemporalDecayC4Calculator:
                 except ValueError:
                     continue
             if date_obj is None:
-                raise ValueError(f"无法解析日期: {target_date}")
+                # 如果无法解析日期，记录警告并返回默认值
+                print(f"警告: 无法解析日期 '{target_date}'，使用默认值'其他'")
+                return "其他"
         elif isinstance(target_date, datetime):
             date_obj = target_date.date()
+        elif isinstance(target_date, (int, float)):
+            # 如果传入的是数字（如0），使用默认值
+            print(f"警告: 传入的日期参数是数字 {target_date}，使用默认值'其他'")
+            return "其他"
         else:
             date_obj = target_date
 

app/utils/industry_calculator.py

@@ -0,0 +1,100 @@
+"""
+行业数据查询和计算工具
+"""
+import logging
+from typing import Optional, Dict, Any
+from app.models.industry import Industry
+
+logger = logging.getLogger(__name__)
+
+
+async def get_industry_data_by_name(industry_name: str) -> Optional[Dict[str, Any]]:
+    """
+    根据行业名称查询行业数据
+    
+    Args:
+        industry_name: 行业名称
+        
+    Returns:
+        包含行业数据的字典，如果未找到则返回None
+        {
+            'code': '行业代码',
+            'name': '行业名称', 
+            'roe': 平均ROE,
+            'fix_num': 行业修正系数,
+            'remark': '备注'
+        }
+    """
+    try:
+        industry = await Industry.filter(name=industry_name).first()
+        if industry:
+            return {
+                'code': industry.code,
+                'name': industry.name,
+                'roe': industry.roe,
+                'fix_num': industry.fix_num,
+                'remark': industry.remark
+            }
+        else:
+            logger.warning(f"未找到行业数据: {industry_name}")
+            return None
+    except Exception as e:
+        logger.error(f"查询行业数据失败: {industry_name}, 错误: {str(e)}")
+        return None
+
+
+async def calculate_industry_average_s2(industry_name: str) -> float:
+    """
+    计算行业均值S2
+    
+    Args:
+        industry_name: 行业名称
+        
+    Returns:
+        行业均值S2，如果查询失败则返回0.0
+    """
+    try:
+        industry_data = await get_industry_data_by_name(industry_name)
+        if industry_data:
+            # S2 = ROE * 修正系数
+            roe = industry_data.get('roe', 0.0)
+            fix_num = industry_data.get('fix_num', 0.0)
+            s2_value = roe * fix_num
+            
+            # 确保S2值为正数，避免对数计算错误
+            if s2_value <= 0:
+                logger.warning(f"行业 {industry_name} S2计算值为负数或零: ROE={roe}, 修正系数={fix_num}, S2={s2_value}，使用默认值0.01")
+                s2_value = 0.01  # 使用小的正数避免对数计算错误
+            
+            logger.info(f"行业 {industry_name} S2计算: ROE={roe}, 修正系数={fix_num}, S2={s2_value}")
+            return s2_value
+        else:
+            logger.warning(f"未找到行业 {industry_name} 的数据，返回默认值0.01")
+            return 0.01  # 返回小的正数而不是0.0
+    except Exception as e:
+        logger.error(f"计算行业均值S2失败: {industry_name}, 错误: {str(e)}")
+        return 0.01  # 返回小的正数而不是0.0
+
+
+async def get_all_industries() -> list:
+    """
+    获取所有行业列表
+    
+    Returns:
+        行业列表
+    """
+    try:
+        industries = await Industry.all()
+        return [
+            {
+                'code': industry.code,
+                'name': industry.name,
+                'roe': industry.roe,
+                'fix_num': industry.fix_num,
+                'remark': industry.remark
+            }
+            for industry in industries
+        ]
+    except Exception as e:
+        logger.error(f"获取行业列表失败: {str(e)}")
+        return []

app/utils/universal_api_manager.py

@@ -237,11 +237,12 @@ class UniversalAPIManager:
                     prepared_params['token'] = api_key
 
         elif provider == 'dajiala':
-            # 微信指数
+            # 微信指数/极致聊接口需要 key 参数
-            # JustOneAPI需要token参数
+            endpoint_config = self._get_endpoint_config(provider, endpoint)
-            api_key = provider_config.get('api_key')
+            if endpoint_config:
-            if api_key:
+                api_key = endpoint_config.get('api_key')
-                prepared_params['key'] = api_key
+                if api_key:
+                    prepared_params['key'] = api_key
 
         elif provider == 'jizhiliao':
             # 极致聊接口需要 key，默认从配置读取
@@ -325,6 +326,9 @@ class UniversalAPIManager:
                         }
                         
                         response = self.session.post(url, json=prepared_params, headers=headers, timeout=timeout)
+                    elif provider == 'dajiala':
+                        # dajiala是微信指数/极致聊接口，使用普通POST请求
+                        response = self.session.post(url, json=prepared_params, timeout=timeout)
                     else:
                         response = self.session.post(url, json=prepared_params, timeout=timeout)
                 else:
@@ -365,6 +369,7 @@ class UniversalAPIManager:
             "sub_search_type": 0,
             "verifycode": ""
         }
+
         return self.make_request('dajiala', 'web_search', data)
 
     def video_views(self,platform_type,video_id):

app/utils/wechat_index_calculator.py

@@ -0,0 +1,131 @@
+"""
+微信指数计算工具
+用于处理微信指数API返回的数据并计算平均值
+"""
+
+from typing import Dict, Any, Optional, List
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+class WeChatIndexCalculator:
+    """微信指数计算器"""
+    
+    @staticmethod
+    def extract_index_data(api_response: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+        从微信指数API响应中提取指数数据
+        
+        Args:
+            api_response: 微信指数API的响应数据
+            
+        Returns:
+            包含指数和时间戳的数据列表
+        """
+        try:
+            # 检查响应状态
+            if api_response.get('code') != 0:
+                logger.error(f"微信指数API返回错误: {api_response}")
+                return []
+            
+            # 提取数据路径: data[0].items[0].itemInfo.data
+            data_list = api_response.get('data', [])
+            if not data_list:
+                logger.warning("微信指数响应中没有数据")
+                return []
+            
+            first_data = data_list[0]
+            items = first_data.get('items', [])
+            if not items:
+                logger.warning("微信指数响应中没有items数据")
+                return []
+            
+            first_item = items[0]
+            item_info = first_item.get('itemInfo', {})
+            index_data = item_info.get('data', [])
+            
+            if not index_data:
+                logger.warning("微信指数响应中没有指数数据")
+                return []
+            
+            logger.info(f"成功提取到 {len(index_data)} 条微信指数数据")
+            return index_data
+            
+        except Exception as e:
+            logger.error(f"提取微信指数数据时发生错误: {e}")
+            return []
+    
+    @staticmethod
+    def calculate_30_day_average(index_data: List[Dict[str, Any]]) -> float:
+        """
+        计算近30天微信指数平均值
+        
+        Args:
+            index_data: 包含指数和时间戳的数据列表
+            
+        Returns:
+            近30天的平均指数值
+        """
+        try:
+            if not index_data:
+                logger.warning("没有指数数据用于计算平均值")
+                return 0.0
+            
+            # 取最近30条数据（如果数据不足30条，则使用所有数据）
+            recent_data = index_data[-30:] if len(index_data) >= 30 else index_data
+            
+            # 提取指数值并转换为数字
+            index_values = []
+            for item in recent_data:
+                try:
+                    index_str = item.get('index', '0')
+                    index_value = float(index_str) if index_str else 0.0
+                    index_values.append(index_value)
+                except (ValueError, TypeError) as e:
+                    logger.warning(f"无法转换指数值 '{item.get('index')}': {e}")
+                    index_values.append(0.0)
+            
+            if not index_values:
+                logger.warning("没有有效的指数值用于计算")
+                return 0.0
+            
+            # 计算平均值
+            total_sum = sum(index_values)
+            count = len(index_values)
+            average = total_sum / count
+            
+            logger.info(f"计算微信指数平均值: {count}天数据，总和={total_sum}，平均值={average:.2f}")
+            return round(average, 2)
+            
+        except Exception as e:
+            logger.error(f"计算微信指数平均值时发生错误: {e}")
+            return 0.0
+    
+    @classmethod
+    def process_wechat_index_response(cls, api_response: Dict[str, Any]) -> float:
+        """
+        处理微信指数API响应，返回近30天平均值
+        
+        Args:
+            api_response: 微信指数API的完整响应
+            
+        Returns:
+            近30天微信指数平均值
+        """
+        try:
+            # 提取指数数据
+            index_data = cls.extract_index_data(api_response)
+            
+            # 计算平均值
+            average_index = cls.calculate_30_day_average(index_data)
+            
+            return average_index
+            
+        except Exception as e:
+            logger.error(f"处理微信指数响应时发生错误: {e}")
+            return 0.0
+
+
+# 创建全局实例
+wechat_index_calculator = WeChatIndexCalculator()