433 lines
18 KiB
Python
433 lines
18 KiB
Python
"""兴邦金租智能评审助手 - 统一API（7 个助手完整版）
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基于 2026.8.18 会议痛点的完整解决方案：
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1. 立项前置风控助手 🔍 - 业务经理风险自查
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2. 中诚信智能填报助手 📊 - 激活十几万投资的评级模板
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3. 空窗期动态监控助手 🚨 - 17天空窗期风险重扫
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4. 保单条款合规核验助手 🛡️ - OCR+条款解析
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5. 评审报告辅助生成助手 📄 - 看资料+写报告提效
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6. 主审员智能分配助手 🎯 - 多维度负荷优化
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7. AI预审过滤+加速助手 🤖 - 团队经验预判+加速
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"""
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import asyncio
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import json
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from datetime import datetime
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from typing import AsyncGenerator, Dict, List, Optional
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from fastapi import APIRouter, HTTPException
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel, Field
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# 导入数据层
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from data_layer.erp_connector import get_erp_connector
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from data_layer.history_store import get_history_store
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from data_layer.reviewer_profile import get_reviewer_store
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from data_layer.team_experience import get_team_experience_store
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router = APIRouter(prefix="/api/xingbang/unified", tags=["兴邦智能评审统一接口"])
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# ============ Pydantic 模型 ============
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class ProjectBasicInfo(BaseModel):
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"""项目基础信息"""
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project_id: str = ""
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project_name: str
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client_name: str
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industry: str
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credit_amount: float # 万元
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lease_object: str = ""
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lease_value: float = 0 # 万元
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class FinancialData(BaseModel):
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"""财务数据"""
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registered_capital: float = 0
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established_years: int = 0
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asset_liability_ratio: float = 0
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current_ratio: float = 0
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quick_ratio: float = 0
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net_profit_2024: float = 0
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net_profit_2025: float = 0
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revenue_growth_rate: float = 0
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class CreditReport(BaseModel):
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"""征信报告"""
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overdue_count: int = 0
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query_count_recent_6m: int = 0
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credit_limit: float = 0
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enforcement_records: int = 0
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class InsurancePolicyData(BaseModel):
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"""保单数据"""
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policy_number: str
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insurance_company: str
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policy_type: str
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coverage_amount: float
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exclusions: List[str] = []
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policy_pdf_path: str = ""
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# ============ 助手 1：立项前置风控 ============
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class Assistant1Request(BaseModel):
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"""立项前置风控请求"""
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project: ProjectBasicInfo
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financial: FinancialData
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credit: CreditReport
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@router.post("/assistant1/risk-check")
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async def assistant1_risk_check(request: Assistant1Request):
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"""助手1：立项前置风控自查（只给风险点，不给结论）"""
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async def generate():
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try:
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# 获取团队经验
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team_exp = get_team_experience_store()
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thresholds = team_exp.get_approval_thresholds()
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risk_patterns = team_exp.get_risk_patterns(request.project.industry)
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red_flags = team_exp.get_industry_red_flags(request.project.industry)
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yield f"data: {json.dumps({'type': 'start'}, ensure_ascii=False)}\n\n"
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# 生成 Markdown 报告
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content = f"""# 立项前置风险自查清单
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## 📋 项目基本信息
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- **项目名称**：{request.project.project_name}
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- **客户名称**：{request.project.client_name}
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- **行业**：{request.project.industry}
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- **授信金额**：{request.project.credit_amount} 万元
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- **租赁物**：{request.project.lease_object or '未填写'}
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- **租赁物价值**：{request.project.lease_value} 万元
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---
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## 🔍 风险自查结果
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"""
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yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
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# 检查高风险项
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high_risks = []
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medium_risks = []
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low_risks = []
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# 1. 客户资质检查
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if request.financial.registered_capital < 1000:
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high_risks.append("**注册资本不足**：注册资本 {:.0f} 万元 < 1000 万元（标准要求）\n - **建议**：考虑提高授信门槛或要求集团担保".format(request.financial.registered_capital))
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if request.financial.established_years < 3:
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medium_risks.append("**成立时间较短**：成立 {} 年 < 3 年（标准要求）\n - **建议**：补充实控人其他企业经营情况".format(request.financial.established_years))
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# 2. 财务指标检查
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asset_liability = request.financial.asset_liability_ratio
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threshold_al = thresholds.get("资产负债率", {})
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if asset_liability > threshold_al.get("critical", 0.8):
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high_risks.append(f"**资产负债率过高**：{asset_liability:.1%} > {threshold_al.get('critical', 0.8):.0%}（警戒线）\n - **团队共识**：{threshold_al.get('team_consensus', '需要额外担保')}")
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elif asset_liability > threshold_al.get("warning", 0.7):
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medium_risks.append(f"**资产负债率偏高**：{asset_liability:.1%}（位于 {threshold_al.get('warning', 0.7):.0%}-{threshold_al.get('critical', 0.8):.0%} 区间）\n - **建议**：补充负债结构说明，关注短期偿债压力")
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else:
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low_risks.append(f"✅ **资产负债率**：{asset_liability:.1%}（良好）")
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current_ratio = request.financial.current_ratio
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threshold_cr = thresholds.get("流动比率", {})
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if current_ratio < threshold_cr.get("critical", 1.0):
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high_risks.append(f"**流动比率不足**：{current_ratio:.2f} < {threshold_cr.get('critical', 1.0):.2f}（红线）\n - **团队共识**：{threshold_cr.get('team_consensus', '短期偿债能力堪忧')}")
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elif current_ratio < threshold_cr.get("warning", 1.2):
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medium_risks.append(f"**流动比率偏低**：{current_ratio:.2f}\n - **建议**：关注应收账款周转情况")
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else:
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low_risks.append(f"✅ **流动比率**：{current_ratio:.2f}（符合标准）")
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# 3. 征信检查
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if request.credit.overdue_count > 0:
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high_risks.append(f"**征信逾期记录**：近 2 年有 {request.credit.overdue_count} 次逾期\n - **建议**：要求客户提供逾期说明及还款证明")
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else:
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low_risks.append("✅ **征信记录**：近 2 年无逾期（良好）")
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if request.credit.enforcement_records > 0:
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high_risks.append(f"**被执行记录**：存在 {request.credit.enforcement_records} 条被执行记录\n - **重要**：评审大概率退回，需先解决执行案件")
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else:
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low_risks.append("✅ **被执行记录**：无（良好）")
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if request.credit.query_count_recent_6m > 10:
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medium_risks.append(f"**征信查询频繁**：近 6 个月查询 {request.credit.query_count_recent_6m} 次\n - **建议**：了解客户融资需求是否过于迫切")
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# 4. 租赁物检查
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if request.project.lease_value > 0:
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coverage_ratio = request.project.lease_value / request.project.credit_amount
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if coverage_ratio < 1.2:
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high_risks.append(f"**租赁物价值不足**：租赁物价值 {request.project.lease_value} 万元，覆盖率 {coverage_ratio:.1%} < 120%（标准要求）\n - **建议**：补充其他担保措施")
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else:
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low_risks.append(f"✅ **租赁物覆盖率**：{coverage_ratio:.1%}（符合要求）")
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# 5. 行业红线检查
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if red_flags:
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content_flags = f"\n### ⚠️ {request.project.industry} 行业常见风险点\n\n"
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for flag in red_flags:
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content_flags += f"- {flag}\n"
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content_flags += "\n**建议**：核实客户是否触及以上风险点\n\n"
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yield f"data: {json.dumps({'type': 'content', 'data': content_flags}, ensure_ascii=False)}\n\n"
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# 输出风险项
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if high_risks:
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content_high = "### 🔴 高风险项（必须处理，否则评审大概率退回）\n\n"
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for i, risk in enumerate(high_risks, 1):
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content_high += f"{i}. {risk}\n\n"
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yield f"data: {json.dumps({'type': 'content', 'data': content_high}, ensure_ascii=False)}\n\n"
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if medium_risks:
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content_medium = "### 🟡 中风险项（建议补充材料或说明）\n\n"
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for i, risk in enumerate(medium_risks, 1):
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content_medium += f"{i}. {risk}\n\n"
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yield f"data: {json.dumps({'type': 'content', 'data': content_medium}, ensure_ascii=False)}\n\n"
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if low_risks:
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content_low = "### 🟢 低风险项（符合要求）\n\n"
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for risk in low_risks:
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content_low += f"- {risk}\n"
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content_low += "\n"
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yield f"data: {json.dumps({'type': 'content', 'data': content_low}, ensure_ascii=False)}\n\n"
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# 整体评估
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if len(high_risks) == 0 and len(medium_risks) == 0:
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suggestion = "✅ **直接提交**：项目风险可控，可直接提交评审"
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elif len(high_risks) == 0:
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suggestion = "🟡 **补充材料后提交**：建议先处理中风险项，提高通过率"
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else:
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suggestion = "🔴 **重大调整后提交**：存在高风险项，建议先与客户沟通调整方案"
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content_final = f"""---
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## 💡 整体评估
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{suggestion}
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**说明**：本清单基于团队历史评审经验生成，仅供参考，不代表评审结论。最终是否通过由主审员独立判断。
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"""
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yield f"data: {json.dumps({'type': 'content', 'data': content_final}, ensure_ascii=False)}\n\n"
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yield f"data: {json.dumps({'type': 'done'}, ensure_ascii=False)}\n\n"
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except Exception as e:
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yield f"data: {json.dumps({'type': 'error', 'message': str(e)}, ensure_ascii=False)}\n\n"
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return StreamingResponse(generate(), media_type="text/event-stream")
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# ============ 助手 6：主审员智能分配 ============
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class Assistant6Request(BaseModel):
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"""主审员智能分配请求"""
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project_industry: str
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project_amount: float # 万元
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project_complexity: int = Field(3, ge=1, le=5, description="项目复杂度 1-5")
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@router.post("/assistant6/allocate")
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async def assistant6_allocate(request: Assistant6Request):
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"""助手6：主审员智能分配（多维度评分）"""
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try:
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reviewer_store = get_reviewer_store()
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# 获取推荐列表
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recommendations = reviewer_store.get_recommended_reviewers(
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project_industry=request.project_industry,
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project_complexity=request.project_complexity,
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top_n=3
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)
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# 获取所有主审员当前状态
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all_profiles = reviewer_store.get_all_profiles()
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reviewer_status = [
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{
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"name": name,
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"current_projects": profile["current_projects"],
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"specialty": profile["specialty"],
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"workload_capacity": profile["workload_capacity"],
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"status": "🔴 超载" if profile["current_projects"] >= profile["workload_capacity"]
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else ("🟡 偏高" if profile["current_projects"] >= profile["workload_capacity"] * 0.8 else "🟢 正常")
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}
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for name, profile in all_profiles.items()
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]
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return {
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"reviewers": reviewer_status,
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"recommendations": recommendations,
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"project_info": {
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"industry": request.project_industry,
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"amount": request.project_amount,
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"complexity": request.project_complexity,
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},
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"algorithm_version": "v1.0_multidim_scoring",
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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# ============ 助手 7：AI预审过滤+加速 ============
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class Assistant7Request(BaseModel):
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"""AI预审请求"""
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project: ProjectBasicInfo
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financial: FinancialData
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credit: CreditReport
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@router.post("/assistant7/pre-screen")
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async def assistant7_pre_screen(request: Assistant7Request):
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"""助手7：AI预审过滤（基于团队经验，快速判断是否值得进入正式评审）"""
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async def generate():
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try:
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yield f"data: {json.dumps({'type': 'start'}, ensure_ascii=False)}\n\n"
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# 获取团队经验和历史案例
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team_exp = get_team_experience_store()
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history_store = get_history_store()
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thresholds = team_exp.get_approval_thresholds()
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rejection_reasons = team_exp.get_common_rejection_reasons(top_n=5)
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# 相似案例检索
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similar_cases = history_store.search_similar_cases(
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industry=request.project.industry,
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credit_amount=request.project.credit_amount,
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limit=3
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)
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content = f"""# AI预审报告（团队经验模式）
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## 📊 项目信息
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- **项目名称**：{request.project.project_name}
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- **客户名称**：{request.project.client_name}
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- **行业**：{request.project.industry}
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- **授信金额**：{request.project.credit_amount} 万元
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---
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## 🤖 AI预审判断（基于团队 {team_exp.get_metadata().get('total_cases_analyzed', 0)} 个历史案例）
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"""
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yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
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# 快速红线检查
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red_line_hit = []
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warning_items = []
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# 1. 财务红线
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if request.financial.asset_liability_ratio > thresholds.get("资产负债率", {}).get("critical", 0.8):
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red_line_hit.append("资产负债率超过红线")
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if request.financial.current_ratio < thresholds.get("流动比率", {}).get("critical", 1.0):
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red_line_hit.append("流动比率低于红线")
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# 2. 征信红线
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if request.credit.enforcement_records > 0:
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red_line_hit.append(f"存在 {request.credit.enforcement_records} 条被执行记录")
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if request.credit.overdue_count > 2:
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red_line_hit.append(f"征信逾期次数过多（{request.credit.overdue_count} 次）")
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# 3. 警告项
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if request.financial.revenue_growth_rate < 0:
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warning_items.append("营收负增长")
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if request.credit.query_count_recent_6m > 10:
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warning_items.append("征信查询频繁")
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# AI预审结论
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if red_line_hit:
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conclusion = "🔴 **不建议进入正式评审**"
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reason_text = "\n".join([f"- {item}" for item in red_line_hit])
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content_conclusion = f"""### {conclusion}
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**触及红线项**：
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{reason_text}
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**建议**：与客户沟通调整方案，或直接退回立项申请，避免浪费评审资源。
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"""
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elif len(warning_items) >= 2:
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conclusion = "🟡 **建议谨慎评审**"
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reason_text = "\n".join([f"- {item}" for item in warning_items])
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content_conclusion = f"""### {conclusion}
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**警告项**：
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{reason_text}
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**建议**：可以进入正式评审，但需重点关注以上风险点，建议增加尽调深度。
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"""
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else:
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conclusion = "🟢 **建议进入正式评审**"
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content_conclusion = f"""### {conclusion}
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**初步判断**：项目风险可控，符合基本准入标准，建议正常推进评审流程。
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"""
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yield f"data: {json.dumps({'type': 'content', 'data': content_conclusion}, ensure_ascii=False)}\n\n"
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# 相似案例参考
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if similar_cases:
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content_cases = "\n---\n\n## 📚 相似案例参考\n\n"
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for i, case in enumerate(similar_cases, 1):
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result_emoji = "✅" if case.get("review_result") == "approved" else "❌"
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content_cases += f"""### 案例 {i}：{case.get('project_name', '未知项目')}
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- **行业**：{case.get('industry', '未知')}
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- **金额**：{case.get('credit_amount', 0)} 万元
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- **评审结果**：{result_emoji} {case.get('review_result', '未知')}
|
||
- **关键风险点**：{', '.join([r.get('type', '未知') for r in case.get('identified_risks', [])])}
|
||
|
||
"""
|
||
yield f"data: {json.dumps({'type': 'content', 'data': content_cases}, ensure_ascii=False)}\n\n"
|
||
|
||
# 高频退回原因提示
|
||
content_tips = "\n---\n\n## 💡 团队经验提示（高频退回原因）\n\n"
|
||
for reason in rejection_reasons:
|
||
content_tips += f"- **{reason['reason']}**（{reason['count']} 次） → {reason['solution']}\n"
|
||
|
||
yield f"data: {json.dumps({'type': 'content', 'data': content_tips}, ensure_ascii=False)}\n\n"
|
||
|
||
yield f"data: {json.dumps({'type': 'done'}, ensure_ascii=False)}\n\n"
|
||
|
||
except Exception as e:
|
||
yield f"data: {json.dumps({'type': 'error', 'message': str(e)}, ensure_ascii=False)}\n\n"
|
||
|
||
return StreamingResponse(generate(), media_type="text/event-stream")
|
||
|
||
|
||
# ============ 数据管理接口 ============
|
||
|
||
@router.get("/data/reviewers")
|
||
async def get_all_reviewers():
|
||
"""获取所有主审员画像"""
|
||
reviewer_store = get_reviewer_store()
|
||
return reviewer_store.get_all_profiles()
|
||
|
||
|
||
@router.get("/data/team-experience")
|
||
async def get_team_experience():
|
||
"""获取团队集体经验"""
|
||
team_exp = get_team_experience_store()
|
||
return {
|
||
"approval_thresholds": team_exp.get_approval_thresholds(),
|
||
"common_rejections": team_exp.get_common_rejection_reasons(),
|
||
"metadata": team_exp.get_metadata(),
|
||
}
|
||
|
||
|
||
@router.get("/data/history-stats")
|
||
async def get_history_statistics():
|
||
"""获取历史案例统计"""
|
||
history_store = get_history_store()
|
||
return history_store.get_statistics()
|