449 lines
20 KiB
Python
449 lines
20 KiB
Python
from fastapi import APIRouter, Depends, HTTPException, status
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from typing import Optional, List, Dict, Any
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import json
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import asyncio
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import time,random
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from app.controllers.user_valuation import user_valuation_controller
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from app.schemas.valuation import (
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UserValuationCreate,
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UserValuationQuery,
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UserValuationList,
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UserValuationOut,
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UserValuationDetail
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)
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from app.schemas.base import Success, SuccessExtra
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from app.utils.app_user_jwt import get_current_app_user_id
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from app.utils.calculation_engine import FinalValueACalculator
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from app.utils.calculation_engine.drp import DynamicPledgeRateCalculator
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from app.utils.calculation_engine.economic_value_b1.sub_formulas.basic_value_b11 import calculate_popularity_score, \
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calculate_infringement_score, calculate_patent_usage_score
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from app.utils.calculation_engine.economic_value_b1.sub_formulas.traffic_factor_b12 import calculate_search_index_s1
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from app.log.log import logger
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from app.models.esg import ESG
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from app.models.industry import Industry
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from app.models.policy import Policy
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from app.utils.universal_api_manager import universal_api
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from app.utils.wechat_index_calculator import wechat_index_calculator
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app_valuations_router = APIRouter(tags=["用户端估值评估"])
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@app_valuations_router.post("/calculation", summary="计算估值")
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async def calculate_valuation(
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data: UserValuationCreate,
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user_id: int = Depends(get_current_app_user_id)
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):
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"""
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计算估值评估
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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
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请求示例JSON (仅包含用户填写部分):
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{
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"asset_name": "传统刺绣工艺",
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"institution": "某文化传承机构",
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"industry": "传统手工艺",
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// 财务状况 (用户填写)
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"annual_revenue": "500", // 近12个月机构营收/万元
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"rd_investment": "50", // 近12个月机构研发投入/万元
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"three_year_income": [400, 450, 500], // 近三年机构收益/万元
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// 非遗等级与技术 (用户填写)
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"inheritor_level": "国家级传承人", // 非遗传承人等级
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"inheritor_ages": [45, 60, 75], // 传承人年龄列表
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"heritage_level": "国家级", // 非遗等级
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"patent_application_no": "CN202310123456.7", // 专利申请号
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"patent_remaining_years": "15", // 专利剩余年限
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"historical_evidence": { // 历史证明证据及数量
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"历史文献": 3,
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"考古发现": 2,
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"传承谱系": 5
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},
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"pattern_images": ["demo.jpg"], // 非遗纹样图片
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// 非遗应用与推广 (用户填写)
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"application_maturity": "成熟应用", // 应用成熟度
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"application_coverage": "全国覆盖", // 应用覆盖范围
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"cooperation_depth": "0.5", // 跨界合作深度
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"offline_activities": "12", // 近12个月线下宣讲活动次数
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"online_accounts": [ // 线上宣传账号信息
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{"platform": "抖音", "account": "传统刺绣大师"},
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{"platform": "微博", "account": "非遗传承人"}
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],
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// 市场信息 (用户填写)
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"sales_volume": "1000", // 近12个月销售量
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"link_views": "5000", // 近12个月链接浏览量
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"circulation": "限量", // 发行量
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"last_market_activity": "2024-01-15", // 最近一次市场活动时间
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"price_fluctuation": [95.0, 105.0], // 近30天价格波动区间
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"manual_bids": [48000.0, 50000.0, 52000.0], // 手动收集的竞价列表
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// 政策相关 (用户填写)
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"funding_status": "国家级资助", // 资金支持情况
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"implementation_stage": "成熟应用" // 实施阶段
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}
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API获取参数 (系统自动获取，无需用户填写):
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- 搜索指数: 百度、微信、微博搜索指数
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- 社交媒体数据: 点赞数、评论数、转发数、粉丝数
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- 交易数据: 近3个月加权平均价格
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- 热度数据: 近7日日均浏览量、收藏数
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- ESG评分: 根据行业自动匹配
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- 行业系数: 根据行业ROE计算
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- 政策匹配度: 根据行业自动匹配
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- 专利验证: 通过API验证专利有效性
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- 侵权记录: 通过API查询侵权诉讼历史
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"""
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try:
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start_ts = time.monotonic()
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logger.info("valuation.calc_start user_id={} asset_name={} industry={}", user_id, getattr(data, 'asset_name', None), getattr(data, 'industry', None))
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# 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）
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esg_obj = None
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industry_obj = None
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policy_obj = None
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try:
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esg_obj = await asyncio.wait_for(ESG.filter(name=data.industry).first(), timeout=2.0)
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except Exception as e:
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logger.warning("valuation.esg_fetch_timeout industry={} err={}", data.industry, repr(e))
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esg_score = float(getattr(esg_obj, 'number', 0.0) or 0.0)
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# 根据行业查询 行业修正系数与ROE
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try:
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industry_obj = await asyncio.wait_for(Industry.filter(name=data.industry).first(), timeout=2.0)
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except Exception as e:
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logger.warning("valuation.industry_fetch_timeout industry={} err={}", data.industry, repr(e))
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fix_num_score = getattr(industry_obj, 'fix_num', 0.0) or 0.0
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# 根据行业查询 政策匹配度
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try:
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policy_obj = await asyncio.wait_for(Policy.filter(name=data.industry).first(), timeout=2.0)
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except Exception as e:
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logger.warning("valuation.policy_fetch_timeout industry={} err={}", data.industry, repr(e))
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policy_match_score = getattr(policy_obj, 'score', 0.0) or 0.0
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# 提取 经济价值B1 计算参数
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input_data_by_b1 = await _extract_calculation_params_b1(data)
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# ESG关联价值 ESG分 (0-10分)
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input_data_by_b1["esg_score"] = esg_score
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# 行业修正系数I
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input_data_by_b1["industry_coefficient"] = fix_num_score
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# 政策匹配度
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input_data_by_b1["policy_match_score"] = policy_match_score
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# 获取专利信息 TODO 参数
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try:
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patent_data = universal_api.query_patent_info("未找到 企业名称、企业统代、企业注册号")
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patent_dict = patent_data if isinstance(patent_data, dict) else {}
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inner_data = patent_dict.get("data", {}) if isinstance(patent_dict.get("data", {}), dict) else {}
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data_list = inner_data.get("dataList", [])
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data_list = data_list if isinstance(data_list, list) else []
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# 验证 专利剩余年限
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# 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)；
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# 发展潜力D相关参数 专利数量
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# 查询匹配申请号的记录集合
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matched = [item for item in data_list if isinstance(item, dict) and item.get("SQH") == getattr(data, 'patent_application_no', None)]
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if matched:
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patent_count = calculate_patent_usage_score(len(matched))
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input_data_by_b1["patent_count"] = float(patent_count)
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else:
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input_data_by_b1["patent_count"] = 0.0
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except Exception as e:
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logger.warning("valuation.patent_api_error err={}", repr(e))
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input_data_by_b1["patent_count"] = 0.0
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# 提取 文化价值B2 计算参数
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input_data_by_b2 = await _extract_calculation_params_b2(data)
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# 提取 风险调整系数B3 计算参数
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input_data_by_b3 = await _extract_calculation_params_b3(data)
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# 提取 市场估值C 参数
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input_data_by_c = await _extract_calculation_params_c(data)
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input_data = {
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# 模型估值B 相关参数
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"model_data": {
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# 经济价值B1 参数
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"economic_data": input_data_by_b1,
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# 文化价值B2 参数
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"cultural_data": input_data_by_b2,
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# 风险调整参数 B3
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"risky_data": input_data_by_b3,
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},
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# 市场估值C 参数
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"market_data": input_data_by_c,
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}
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calculator = FinalValueACalculator()
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# 计算最终估值A（统一计算）
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calculation_result = await calculator.calculate_complete_final_value_a(input_data)
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# 计算动态质押
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drp_c = DynamicPledgeRateCalculator()
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'''
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monthly_amount (float): 月交易额（万元）
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heritage_level (str): 非遗等级
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'''
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# 解析月交易额字符串为数值
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monthly_amount = drp_c.parse_monthly_transaction_amount(data.monthly_transaction_amount or "")
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drp_result = drp_c.calculate_dynamic_pledge_rate(monthly_amount, data.heritage_asset_level)
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# 结构化日志：关键分值
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try:
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duration_ms = int((time.monotonic() - start_ts) * 1000)
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logger.info(
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"valuation.calc_done user_id={} duration_ms={} model_value_b={} market_value_c={} final_value_ab={}",
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user_id,
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duration_ms,
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calculation_result.get('model_value_b'),
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calculation_result.get('market_value_c'),
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calculation_result.get('final_value_ab'),
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)
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except Exception:
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pass
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# 创建估值评估记录
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result = await user_valuation_controller.create_valuation(
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user_id=user_id,
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data=data,
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calculation_result=calculation_result,
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calculation_input={
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'model_data': {
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'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()),
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'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()),
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'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()),
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},
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'market_data': list(input_data.get('market_data', {}).keys()),
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},
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drp_result=drp_result
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)
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# 组装返回
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result_dict = json.loads(result.model_dump_json())
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result_dict['calculation_result'] = calculation_result
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result_dict['calculation_input'] = {
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'model_data': {
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'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()),
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'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()),
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'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()),
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},
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'market_data': list(input_data.get('market_data', {}).keys()),
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}
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return Success(data=result_dict, msg="估值计算完成")
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except Exception as e:
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logger.error("valuation.calc_failed user_id={} err={}", user_id, repr(e))
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raise HTTPException(status_code=400, detail=f"计算失败: {str(e)}")
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async def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]:
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"""
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从用户提交的数据中提取计算所需的参数
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Args:
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data: 用户提交的估值评估数据
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Returns:
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Dict: 计算所需的参数字典
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"""
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# 基础价值B11相关参数
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# 财务价值所需数据 从近三年收益计算
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three_year_income = data.three_year_income or [0, 0, 0]
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# 法律强度L相关参数
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# 普及地域分值 默认 7分
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popularity_score = calculate_popularity_score(data.application_coverage)
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# 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)
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infringement_score = calculate_infringement_score("无侵权信息")
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infringement_score = 0
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# 创新投入比 = (研发费用/营收) * 100
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try:
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rd_investment = float(data.rd_investment or 0)
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annual_revenue = float(data.annual_revenue or 1) # 避免除零
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innovation_ratio = (rd_investment / annual_revenue) * 100 if annual_revenue > 0 else 0
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except (ValueError, TypeError):
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innovation_ratio = 0.0
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# 流量因子B12相关参数
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# 近30天搜索指数S1 - 使用微信指数除以10计算
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wechat_index = wechat_index_calculator.process_wechat_index_response(universal_api.wx_index(data.asset_name)) # 通过资产信息获取微信指数
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search_index_s1 = calculate_search_index_s1(wechat_index) # S1 = 微信指数 / 10
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# 行业均值S2 TODO 系统内置 未找到相关内容
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industry_average_s2 = 0.0
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# 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
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# likes: 点赞数(API获取)
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# comments: 评论数(API获取)
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# shares: 转发数(API获取)
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# followers: 粉丝数
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# click_count: 商品链接点击量(用户填写) sales_volume 使用 sales_volume 销售量
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# view_count: 内容浏览量(用户填写) link_views
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# 政策乘数B13相关参数
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# 政策契合度评分P - 根据行业和资助情况计算
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# 实施阶段
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implementation_stage = data.application_maturity
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# 资金支持
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funding_support = data.funding_status
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return {
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# 基础价值B11相关参数
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'three_year_income': three_year_income,
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'popularity_score': popularity_score,
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'infringement_score': infringement_score,
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'innovation_ratio': innovation_ratio,
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# 流量因子B12相关参数
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'search_index_s1': search_index_s1,
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'industry_average_s2': industry_average_s2,
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# 'social_media_spread_s3': social_media_spread_s3,
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# 这些社交数据暂未来源，置为0，后续接入API再填充
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'likes': 0,
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'comments': 0,
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'shares': 0,
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# followers 非当前计算用键，先移除避免干扰
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# click_count 与 view_count 目前未参与计算，先移除
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# 政策乘数B13相关参数
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'implementation_stage': implementation_stage,
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'funding_support':funding_support
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}
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# 获取 文化价值B2 相关参数
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async def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, Any]:
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"""
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argrg:
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data: 用户提交的估值评估数据
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retus:
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Dict: 计算所需的参数字典
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"""
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# 导入计算器来转换传承人等级
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from app.utils.calculation_engine.cultural_value_b2.sub_formulas.living_heritage_b21 import LivingHeritageB21Calculator
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# 活态传承系数B21 县官参数
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living_heritage_calculator = LivingHeritageB21Calculator()
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inheritor_level = data.inheritor_level or "市级传承人" # 设置默认值
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inheritor_level_coefficient = living_heritage_calculator.calculate_inheritor_level_coefficient(inheritor_level)
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offline_sessions = int(data.offline_activities) #线下传习次数
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# 以下调用API douyin\bilibili\kuaishou
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douyin_views = 0
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kuaishou_views= 0
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bilibili_views= 0
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# 跨界合作深度：将枚举映射为分值
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# 前端传入的是数字字符串 ("0", "1", "2", "3")，后端也支持中文标签
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depth_mapping = {
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# 前端传入的数字字符串
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"0": 0.0, # 无
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"1": 3.0, # 品牌联名
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"2": 5.0, # 科技载体
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"3": 10.0, # 国家外交礼品
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# 兼容中文标签（以防其他入口传入）
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"无": 0.0,
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"品牌联名": 3.0,
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"科技载体": 5.0,
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"国家外交礼品": 10.0,
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}
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depth_val = str(data.cooperation_depth) if data.cooperation_depth else "0"
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cross_border_depth = depth_mapping.get(depth_val, 0.0)
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# 纹样基因值B22相关参数
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# 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
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historical_inheritance = 0.8
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structure_complexity = 0.75
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normalized_entropy = 0.85
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return {
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"inheritor_level_coefficient": inheritor_level_coefficient,
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"offline_sessions": offline_sessions,
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"douyin_views": douyin_views,
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"kuaishou_views": kuaishou_views,
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||
"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
|
||
price_fluctuation = [float(i) for i in data.price_fluctuation ]
|
||
highest_price,lowest_price= max(price_fluctuation), min(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 = [random.uniform(0, 1) for _ in range(3)]
|
||
expert_valuations = 0 # 默认 0
|
||
# 浏览热度分 TODO 需要先确定平台信息
|
||
# 优化后的多平台数据结构，支持从platform_accounts中提取或使用默认值
|
||
default_platform_data = {
|
||
"bilibili": {
|
||
"account": "default_account",
|
||
"likes": "100",
|
||
"comments": "50",
|
||
"shares": "20",
|
||
"views": "500"
|
||
}
|
||
}
|
||
|
||
# 如果有平台账户数据，尝试提取浏览量，否则使用默认值
|
||
if hasattr(data, 'platform_accounts') and data.platform_accounts:
|
||
platform_accounts_data = data.platform_accounts
|
||
# 获取第一个平台的数据
|
||
first_platform_key = next(iter(platform_accounts_data))
|
||
first_platform_data = platform_accounts_data[first_platform_key]
|
||
# 尝试获取浏览量，如果没有则使用默认值
|
||
daily_browse_volume = float(first_platform_data.get("views", "500"))
|
||
else:
|
||
daily_browse_volume = 500.0 # 默认值
|
||
|
||
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
|
||
}
|