feat: restore risk assessment workspace and improve page scrolling
This commit is contained in:
NathanAlex7
+150
-1
@@ -3,6 +3,7 @@
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import json
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import os
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import traceback
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from pathlib import Path
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from typing import AsyncGenerator
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from fastapi import APIRouter
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@@ -80,7 +81,7 @@ async def event_generator(message: str, session_id: str) -> AsyncGenerator[dict,
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segments: list[dict] = [] # finalized segments
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current_segment: dict = {"content": "", "tool_calls": []}
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async for event in agent_manager.astream(message, history):
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async for event in agent_manager.astream(message, history, session_id):
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event_type = event.get("type", "unknown")
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if event_type == "retrieval":
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@@ -186,3 +187,151 @@ async def chat(request: ChatRequest):
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# Non-streaming fallback
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result = await agent_manager.ainvoke(request.message, request.session_id)
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return {"reply": result}
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@router.get("/chat/raw-traces")
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async def get_raw_traces(session_id: str = "default", limit: int = 20):
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"""获取指定 session 的原始 LLM 调用报文
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Args:
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session_id: 会话 ID
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limit: 返回最近 N 条记录 (默认 20)
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Returns:
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{"traces": [...]} 原始报文列表，按时间倒序
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"""
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try:
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from graph.raw_trace import load_raw_traces
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# 从 agent_manager 获取 raw_logs_dir
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raw_logs_dir = agent_manager._raw_logs_dir
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if not raw_logs_dir:
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return {"traces": []}
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traces = load_raw_traces(session_id, raw_logs_dir, limit=limit)
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return {"traces": traces}
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except Exception as e:
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traceback.print_exc()
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return {"traces": [], "error": str(e)}
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@router.get("/chat/trajectory")
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async def get_trajectory(session_id: str = "default"):
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"""获取会话完整交互轨迹 - 包含完整的 human/assistant/tool 消息流
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Args:
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session_id: 会话 ID
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Returns:
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{
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"session_id": "...",
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"messages": [
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{"role": "human", "content": "...", "timestamp": ...},
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{"role": "assistant", "content": "...", "timestamp": ..., "tool_calls": [...]},
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{"role": "tool", "name": "...", "content": "...", "timestamp": ...},
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{"role": "assistant", "content": "...", "timestamp": ...}
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],
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"steps": [...] // 保留旧格式用于向后兼容
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}
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"""
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try:
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import json
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from graph.raw_trace import load_raw_traces
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raw_logs_dir = agent_manager._raw_logs_dir
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if not raw_logs_dir:
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# 无 raw_logs_dir，返回空
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return {"session_id": session_id, "messages": [], "steps": []}
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# 优先读取完整消息流日志文件
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msgs_log_file = raw_logs_dir / f"{session_id}.msgs.jsonl"
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messages = []
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if msgs_log_file.exists():
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# 从 msgs.jsonl 读取完整消息流（包含 tool 消息）
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with open(msgs_log_file, "r", encoding="utf-8") as f:
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for line in f:
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line = line.strip()
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if line:
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try:
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msg = json.loads(line)
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messages.append(msg)
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except json.JSONDecodeError:
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continue
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else:
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# 回退到旧逻辑：从 session 文件读取（无 tool 消息）
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session_messages = session_manager.load_session(session_id)
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for msg in session_messages:
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messages.append({
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"role": msg["role"],
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"content": msg["content"],
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"timestamp": None,
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})
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# 构建旧格式 steps（向后兼容）
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steps = []
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traces = load_raw_traces(session_id, raw_logs_dir, limit=1000)
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traces.sort(key=lambda x: x.get("timestamp_start", 0))
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# 按 user/assistant 消息构建 steps（忽略 tool 消息）
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session_messages = session_manager.load_session(session_id)
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assistant_count = sum(1 for m in session_messages if m["role"] == "assistant")
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for msg_idx, msg in enumerate(session_messages):
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step = {
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"role": msg["role"],
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"content": msg["content"],
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"timestamp": None,
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}
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if msg["role"] == "assistant":
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llm_calls = []
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assistant_seq = sum(1 for m in session_messages[:msg_idx+1] if m["role"] == "assistant")
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traces_per_assistant = len(traces) / max(assistant_count, 1)
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start_trace = int((assistant_seq - 1) * traces_per_assistant)
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end_trace = int(assistant_seq * traces_per_assistant)
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for i in range(start_trace, min(end_trace, len(traces))):
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trace = traces[i]
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llm_call = {
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"model": trace.get("request", {}).get("model", "unknown"),
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"finish_reason": trace.get("finish_reason", "unknown"),
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"request_messages": trace.get("request", {}).get("messages", []),
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"response_text": "",
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"tool_calls_list": [],
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"usage": trace.get("usage", {}),
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"duration_ms": trace.get("duration_ms", 0),
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}
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response_gens = trace.get("response", {}).get("generations", [])
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if response_gens:
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llm_call["response_text"] = response_gens[0].get("text", "")
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msg_data = response_gens[0].get("message", {})
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if isinstance(msg_data, dict) and "tool_calls" in msg_data:
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tool_calls = msg_data["tool_calls"]
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if tool_calls:
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llm_call["tool_calls_list"] = [
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{
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"name": tc.get("name", "") if isinstance(tc, dict) else getattr(tc, "name", ""),
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"args": tc.get("args", {}) if isinstance(tc, dict) else getattr(tc, "args", {}),
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}
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for tc in tool_calls
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]
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llm_calls.append(llm_call)
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if step["timestamp"] is None:
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step["timestamp"] = trace.get("timestamp_start")
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step["llm_calls"] = llm_calls
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steps.append(step)
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return {
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"session_id": session_id,
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"messages": messages, # 新格式：完整消息流（含 tool）
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"steps": steps, # 旧格式：向后兼容
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}
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except Exception as e:
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traceback.print_exc()
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return {"session_id": session_id, "messages": [], "steps": [], "error": str(e)}
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File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,617 @@
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"""
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Agent 1: 风险研判助手 API（双轨驱动版）
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"""
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from fastapi import APIRouter
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from pydantic import BaseModel
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from typing import List, Dict, Any, Optional, Union
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from datetime import datetime
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router = APIRouter(tags=["risk-assess"])
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# ==================== 请求/响应模型 ====================
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class RiskAssessRequest(BaseModel):
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customer_name: str
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project_type: str
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amount: float
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debt_ratio: float
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credit_query_count: int
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litigation_count: int
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external_guarantee: float
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# ==================== API端点 ====================
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@router.post("/analyze")
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async def analyze_risk(req: dict):
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"""风险研判分析（双轨驱动）- 返回伪造的完整数据"""
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# 直接从dict中获取数据
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customer_name = req.get("customer_name", "")
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project_type = req.get("project_type", "")
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amount = float(req.get("amount", 0))
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debt_ratio = float(req.get("debt_ratio", 0))
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credit_query_count = int(req.get("credit_query_count", 0))
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litigation_count = int(req.get("litigation_count", 0))
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external_guarantee = float(req.get("external_guarantee", 0))
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# 生成完整的伪造数据
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risk_items = []
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# 风险项1: 资产负债率
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if req.debt_ratio >= 0.60:
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risk_items.append({
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"level": "high",
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"title": "资产负债率接近红线",
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"description": f"{req.customer_name}资产负债率为 {req.debt_ratio*100:.1f}%，距离70%红线仅剩 {(0.70-req.debt_ratio)*100:.1f}% 空间。",
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"evidence": {
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"rule_based": {
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"source": "《融资租赁评审手册》第12条",
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"page": 12,
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"extracted_by": "AI自动提取（已通过人工审核）",
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"confidence": 0.87
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},
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"data_based": {
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"sample_size": 23,
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"time_range": "过去12个月",
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"decision_stats": [
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{"decision": "降额通过", "percentage": 60.9, "count": 14, "avg_processing_days": 4.2},
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{"decision": "退回补充材料", "percentage": 26.1, "count": 6, "avg_processing_days": 7.5},
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{"decision": "附加条件通过", "percentage": 13.0, "count": 3, "avg_processing_days": 5.8}
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],
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"similar_cases": [
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{
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"case_id": "CAS-2025-08-156",
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"customer_name": "华东光伏设备公司",
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"decision": "降额通过（降15%）",
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"mitigation": "增加法人个人担保，提供政府补贴承诺函"
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},
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{
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"case_id": "CAS-2025-07-089",
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"customer_name": "绿能公交运营公司",
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"decision": "降额通过（降12%）",
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"mitigation": "调整还款期限，追加车辆抵押"
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},
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{
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"case_id": "CAS-2025-06-234",
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"customer_name": "中部新能源投资",
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"decision": "附加条件通过",
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"mitigation": "要求季度现金流报告，设置财务预警指标"
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}
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]
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}
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},
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"suggestion": "建议业务经理提前准备降额方案或增加抵押物，避免评审会直接退回。",
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"smart_recommendation": {
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"primary_action": f"主动降低授信额度12-15%（约 {req.amount * 0.12:.1f}-{req.amount * 0.15:.1f} 亿元），调整后负债率可控",
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"alternative_actions": [
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f"增加抵押物或第三方担保，覆盖率≥授信额度的20%（约 {req.amount * 0.20:.1f} 亿元）",
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"提供详细现金流测算报告，证明偿债能力充足",
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"调整还款期限，降低单期还款压力"
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],
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"reference_case": {
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"case_id": "CAS-2025-08-156",
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"customer_name": "华东光伏设备公司",
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"scenario": f"债务率 {req.debt_ratio*100:.1f}%，新能源行业，申请 {req.amount:.1f} 亿授信",
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"outcome": "降额15%后通过，增加法人担保 + 政府补贴承诺函"
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}
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}
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})
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# 风险项2: 征信查询
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if req.credit_query_count >= 6:
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risk_items.append({
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"level": "medium",
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"title": "征信查询次数偏多",
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"description": f"{req.customer_name}近6个月征信查询 {req.credit_query_count} 次，高于行业平均（4次）。",
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"evidence": {
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"rule_based": {
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"source": "《融资租赁评审手册》第8条 - 征信管理",
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"page": 8,
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"extracted_by": "AI自动提取（已通过人工审核）",
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"confidence": 0.82
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},
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"data_based": {
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"sample_size": 15,
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"time_range": "过去12个月",
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"decision_stats": [
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{"decision": "正常通过", "percentage": 53.3, "count": 8, "avg_processing_days": 3.5},
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{"decision": "要求补充说明", "percentage": 33.3, "count": 5, "avg_processing_days": 5.2},
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{"decision": "降额通过", "percentage": 13.3, "count": 2, "avg_processing_days": 6.0}
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],
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"similar_cases": [
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{
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"case_id": "CAS-2025-09-012",
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"customer_name": "东方物流集团",
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"decision": "正常通过",
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"mitigation": "提供多头融资说明（用于业务扩张），核实无实质风险"
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}
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]
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}
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},
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"suggestion": "建议业务经理核实客户是否存在多头融资，了解征信查询原因（业务扩张 vs 资金紧张）。",
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"smart_recommendation": {
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"primary_action": "要求客户提供征信查询原因说明书，核实多头融资情况",
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"alternative_actions": [
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"提供资金用途说明和还款计划，证明融资用于业务扩张",
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"补充近6个月银行流水，证明现金流充足"
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],
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"reference_case": {
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"case_id": "CAS-2025-09-012",
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"customer_name": "东方物流集团",
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"scenario": f"征信查询 {req.credit_query_count} 次，用于扩张业务",
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"outcome": "提供业务扩张说明后正常通过，核实无资金链风险"
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}
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}
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})
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# 风险项3: 涉诉记录
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if req.litigation_count >= 2:
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risk_items.append({
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"level": "medium",
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"title": "存在涉诉记录",
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"description": f"{req.customer_name}存在 {req.litigation_count} 起涉诉记录，需核实诉讼性质和金额。",
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"evidence": {
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"rule_based": {
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"source": "《融资租赁评审手册》第10条 - 法律风险评估",
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"page": 10,
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"extracted_by": "AI自动提取（已通过人工审核）",
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"confidence": 0.85
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},
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"data_based": {
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"sample_size": 12,
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"time_range": "过去12个月",
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"decision_stats": [
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{"decision": "正常通过", "percentage": 58.3, "count": 7, "avg_processing_days": 4.0},
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{"decision": "要求提供诉讼详情", "percentage": 33.3, "count": 4, "avg_processing_days": 6.5},
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{"decision": "附加条件通过", "percentage": 8.3, "count": 1, "avg_processing_days": 8.0}
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],
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"similar_cases": [
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{
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"case_id": "CAS-2025-08-203",
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"customer_name": "华泰建设工程",
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"decision": "正常通过",
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"mitigation": "确认为小额合同纠纷（<50万），不影响偿债能力"
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}
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]
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}
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},
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"suggestion": "建议业务经理提供每起诉讼的详细情况（原告/被告、金额、进展），评估对财务的影响。",
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"smart_recommendation": {
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"primary_action": "提供诉讼清单（案由、金额、当前状态），说明对财务状况的影响评估",
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"alternative_actions": [
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"如为小额合同纠纷（<50万/起），提供说明后影响较小",
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"提供法律顾问意见书，说明诉讼风险可控"
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],
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"reference_case": {
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"case_id": "CAS-2025-08-203",
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"customer_name": "华泰建设工程",
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"scenario": f"{req.litigation_count} 起小额合同纠纷，总金额<100万",
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"outcome": "确认为日常经营纠纷，不影响偿债能力，正常通过"
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}
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}
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})
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# 风险项4: 对外担保
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guarantee_ratio = req.external_guarantee / req.amount if req.amount > 0 else 0
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if guarantee_ratio >= 0.8:
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risk_items.append({
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"level": "high",
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"title": "对外担保金额较大",
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"description": f"{req.customer_name}对外担保 {req.external_guarantee:.1f} 亿元，为本次申请金额的 {guarantee_ratio:.1f} 倍。",
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"evidence": {
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"rule_based": {
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"source": "《融资租赁评审手册》第11条 - 担保风险",
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"page": 11,
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"extracted_by": "AI自动提取（已通过人工审核）",
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"confidence": 0.88
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},
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"data_based": {
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"sample_size": 18,
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"time_range": "过去12个月",
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"decision_stats": [
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{"decision": "要求提供担保详情", "percentage": 66.7, "count": 12, "avg_processing_days": 5.8},
|
||||
{"decision": "降额通过", "percentage": 22.2, "count": 4, "avg_processing_days": 7.2},
|
||||
{"decision": "附加条件通过", "percentage": 11.1, "count": 2, "avg_processing_days": 6.5}
|
||||
],
|
||||
"similar_cases": [
|
||||
{
|
||||
"case_id": "CAS-2025-07-234",
|
||||
"customer_name": "华信集团",
|
||||
"decision": "附加条件通过",
|
||||
"mitigation": "提供被担保方财务报告，设置代偿预警机制"
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"suggestion": "建议业务经理提供对外担保明细（被担保方、金额、期限），评估代偿风险。",
|
||||
"smart_recommendation": {
|
||||
"primary_action": "提供对外担保明细清单，包括被担保方资质、财务状况、代偿可能性评估",
|
||||
"alternative_actions": [
|
||||
"说明被担保方为关联公司/优质客户，代偿风险低",
|
||||
f"考虑降低授信额度至 {req.amount * 0.8:.1f} 亿元，降低风险敞口"
|
||||
],
|
||||
"reference_case": {
|
||||
"case_id": "CAS-2025-07-234",
|
||||
"customer_name": "华信集团",
|
||||
"scenario": f"对外担保为申请额度的 {guarantee_ratio:.1f} 倍",
|
||||
"outcome": "提供被担保方财务报告，设置代偿预警，附加条件通过"
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
# 风险项5: 行业风险
|
||||
if req.project_type == "对公新能源":
|
||||
risk_items.append({
|
||||
"level": "medium",
|
||||
"title": "新能源行业政策依赖性",
|
||||
"description": f"{req.customer_name}属于新能源行业，收入可能依赖政府补贴，需关注补贴到位情况。",
|
||||
"evidence": {
|
||||
"rule_based": {
|
||||
"source": "《行业风险指引》第3条 - 新能源行业",
|
||||
"page": 3,
|
||||
"extracted_by": "AI自动提取（已通过人工审核）",
|
||||
"confidence": 0.90
|
||||
},
|
||||
"data_based": {
|
||||
"sample_size": 31,
|
||||
"time_range": "过去12个月",
|
||||
"decision_stats": [
|
||||
{"decision": "正常通过", "percentage": 48.4, "count": 15, "avg_processing_days": 4.5},
|
||||
{"decision": "要求补贴承诺函", "percentage": 38.7, "count": 12, "avg_processing_days": 6.2},
|
||||
{"decision": "附加条件通过", "percentage": 12.9, "count": 4, "avg_processing_days": 7.0}
|
||||
],
|
||||
"similar_cases": [
|
||||
{
|
||||
"case_id": "CAS-2025-09-067",
|
||||
"customer_name": "绿动公交集团",
|
||||
"decision": "正常通过",
|
||||
"mitigation": "补贴延迟但现金流充足，运营收入稳定"
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"suggestion": "建议业务经理提供政府补贴承诺函、历史补贴到位情况，说明现金流不完全依赖补贴。",
|
||||
"smart_recommendation": {
|
||||
"primary_action": "要求提供地方政府补贴承诺函，核实历史补贴到位率（建议≥80%）",
|
||||
"alternative_actions": [
|
||||
"提供运营收入构成，证明补贴占比<40%，现金流多元化",
|
||||
"说明补贴延迟应对预案（如银行授信、应收账款保理）"
|
||||
],
|
||||
"reference_case": {
|
||||
"case_id": "CAS-2025-09-067",
|
||||
"customer_name": "绿动公交集团",
|
||||
"scenario": "新能源公交运营，补贴延迟但运营收入稳定",
|
||||
"outcome": "证明运营收入占比65%，补贴延迟不影响还款，正常通过"
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
# 统计汇总
|
||||
high_count = sum(1 for r in risk_items if r["level"] == "high")
|
||||
medium_count = sum(1 for r in risk_items if r["level"] == "medium")
|
||||
low_count = sum(1 for r in risk_items if r["level"] == "low")
|
||||
|
||||
# 提取关注领域
|
||||
focus_areas = []
|
||||
if any("资产负债率" in r["title"] for r in risk_items):
|
||||
focus_areas.append("财务杠杆")
|
||||
if any("征信" in r["title"] for r in risk_items):
|
||||
focus_areas.append("信用状况")
|
||||
if any("涉诉" in r["title"] for r in risk_items):
|
||||
focus_areas.append("法律风险")
|
||||
if any("担保" in r["title"] for r in risk_items):
|
||||
focus_areas.append("对外担保")
|
||||
if any("行业" in r["title"] or "政策" in r["title"] for r in risk_items):
|
||||
focus_areas.append("行业风险")
|
||||
|
||||
if not focus_areas:
|
||||
focus_areas = ["租赁物合规", "现场尽调"]
|
||||
|
||||
# 计算综合置信度
|
||||
total_confidence = sum(r["evidence"]["rule_based"]["confidence"] for r in risk_items) / len(risk_items) if risk_items else 0.95
|
||||
|
||||
# 计算数据覆盖
|
||||
total_samples = sum(r["evidence"]["data_based"]["sample_size"] for r in risk_items)
|
||||
data_coverage = f"{total_samples} 个案例"
|
||||
|
||||
return {
|
||||
"customer_name": req.customer_name,
|
||||
"analysis_timestamp": datetime.now().isoformat(),
|
||||
"risk_items": risk_items,
|
||||
"summary": {
|
||||
"high_count": high_count,
|
||||
"medium_count": medium_count,
|
||||
"low_count": low_count,
|
||||
"focus_areas": focus_areas,
|
||||
"overall_confidence": round(total_confidence, 2),
|
||||
"data_coverage": data_coverage
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@router.get("/test")
|
||||
async def test_endpoint():
|
||||
"""测试端点 - 返回完整的伪造数据"""
|
||||
return {
|
||||
"customer_name": "远东新能源公交公司",
|
||||
"analysis_timestamp": datetime.now().isoformat(),
|
||||
"risk_items": [
|
||||
{
|
||||
"level": "high",
|
||||
"title": "资产负债率接近红线",
|
||||
"description": "远东新能源公交公司资产负债率为 65.0%，距离70%红线仅剩 5.0% 空间。",
|
||||
"evidence": {
|
||||
"rule_based": {
|
||||
"source": "《融资租赁评审手册》第12条",
|
||||
"page": 12,
|
||||
"extracted_by": "AI自动提取（已通过人工审核）",
|
||||
"confidence": 0.87
|
||||
},
|
||||
"data_based": {
|
||||
"sample_size": 23,
|
||||
"time_range": "过去12个月",
|
||||
"decision_stats": [
|
||||
{"decision": "降额通过", "percentage": 60.9, "count": 14, "avg_processing_days": 4.2},
|
||||
{"decision": "退回补充材料", "percentage": 26.1, "count": 6, "avg_processing_days": 7.5},
|
||||
{"decision": "附加条件通过", "percentage": 13.0, "count": 3, "avg_processing_days": 5.8}
|
||||
],
|
||||
"similar_cases": [
|
||||
{
|
||||
"case_id": "CAS-2025-08-156",
|
||||
"customer_name": "华东光伏设备公司",
|
||||
"decision": "降额通过（降15%）",
|
||||
"mitigation": "增加法人个人担保，提供政府补贴承诺函"
|
||||
},
|
||||
{
|
||||
"case_id": "CAS-2025-07-089",
|
||||
"customer_name": "绿能公交运营公司",
|
||||
"decision": "降额通过（降12%）",
|
||||
"mitigation": "调整还款期限，追加车辆抵押"
|
||||
},
|
||||
{
|
||||
"case_id": "CAS-2025-06-234",
|
||||
"customer_name": "中部新能源投资",
|
||||
"decision": "附加条件通过",
|
||||
"mitigation": "要求季度现金流报告，设置财务预警指标"
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"suggestion": "建议业务经理提前准备降额方案或增加抵押物，避免评审会直接退回。",
|
||||
"smart_recommendation": {
|
||||
"primary_action": "主动降低授信额度12-15%（约 0.36-0.45 亿元），调整后负债率可控",
|
||||
"alternative_actions": [
|
||||
"增加抵押物或第三方担保，覆盖率≥授信额度的20%（约 0.60 亿元）",
|
||||
"提供详细现金流测算报告，证明偿债能力充足",
|
||||
"调整还款期限，降低单期还款压力"
|
||||
],
|
||||
"reference_case": {
|
||||
"case_id": "CAS-2025-08-156",
|
||||
"customer_name": "华东光伏设备公司",
|
||||
"scenario": "债务率 65.0%，新能源行业，申请 3.0 亿授信",
|
||||
"outcome": "降额15%后通过，增加法人担保 + 政府补贴承诺函"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"level": "medium",
|
||||
"title": "征信查询次数偏多",
|
||||
"description": "远东新能源公交公司近6个月征信查询 8 次，高于行业平均（4次）。",
|
||||
"evidence": {
|
||||
"rule_based": {
|
||||
"source": "《融资租赁评审手册》第8条 - 征信管理",
|
||||
"page": 8,
|
||||
"extracted_by": "AI自动提取（已通过人工审核）",
|
||||
"confidence": 0.82
|
||||
},
|
||||
"data_based": {
|
||||
"sample_size": 15,
|
||||
"time_range": "过去12个月",
|
||||
"decision_stats": [
|
||||
{"decision": "正常通过", "percentage": 53.3, "count": 8, "avg_processing_days": 3.5},
|
||||
{"decision": "要求补充说明", "percentage": 33.3, "count": 5, "avg_processing_days": 5.2},
|
||||
{"decision": "降额通过", "percentage": 13.3, "count": 2, "avg_processing_days": 6.0}
|
||||
],
|
||||
"similar_cases": [
|
||||
{
|
||||
"case_id": "CAS-2025-09-012",
|
||||
"customer_name": "东方物流集团",
|
||||
"decision": "正常通过",
|
||||
"mitigation": "提供多头融资说明（用于业务扩张），核实无实质风险"
|
||||
},
|
||||
{
|
||||
"case_id": "CAS-2025-07-145",
|
||||
"customer_name": "鑫盛商贸公司",
|
||||
"decision": "要求补充说明",
|
||||
"mitigation": "说明征信查询原因，提供现金流充足证明"
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"suggestion": "建议业务经理核实客户是否存在多头融资，了解征信查询原因（业务扩张 vs 资金紧张）。",
|
||||
"smart_recommendation": {
|
||||
"primary_action": "要求客户提供征信查询原因说明书，核实多头融资情况",
|
||||
"alternative_actions": [
|
||||
"提供资金用途说明和还款计划，证明融资用于业务扩张",
|
||||
"补充近6个月银行流水，证明现金流充足",
|
||||
"如为临时资金需求，提供订单合同等业务凭证"
|
||||
],
|
||||
"reference_case": {
|
||||
"case_id": "CAS-2025-09-012",
|
||||
"customer_name": "东方物流集团",
|
||||
"scenario": "征信查询 8 次，用于扩张业务",
|
||||
"outcome": "提供业务扩张说明后正常通过，核实无资金链风险"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"level": "medium",
|
||||
"title": "存在涉诉记录",
|
||||
"description": "远东新能源公交公司存在 2 起涉诉记录，需核实诉讼性质和金额。",
|
||||
"evidence": {
|
||||
"rule_based": {
|
||||
"source": "《融资租赁评审手册》第10条 - 法律风险评估",
|
||||
"page": 10,
|
||||
"extracted_by": "AI自动提取（已通过人工审核）",
|
||||
"confidence": 0.85
|
||||
},
|
||||
"data_based": {
|
||||
"sample_size": 12,
|
||||
"time_range": "过去12个月",
|
||||
"decision_stats": [
|
||||
{"decision": "正常通过", "percentage": 58.3, "count": 7, "avg_processing_days": 4.0},
|
||||
{"decision": "要求提供诉讼详情", "percentage": 33.3, "count": 4, "avg_processing_days": 6.5},
|
||||
{"decision": "附加条件通过", "percentage": 8.3, "count": 1, "avg_processing_days": 8.0}
|
||||
],
|
||||
"similar_cases": [
|
||||
{
|
||||
"case_id": "CAS-2025-08-203",
|
||||
"customer_name": "华泰建设工程",
|
||||
"decision": "正常通过",
|
||||
"mitigation": "确认为小额合同纠纷（<50万），不影响偿债能力"
|
||||
},
|
||||
{
|
||||
"case_id": "CAS-2025-06-178",
|
||||
"customer_name": "顺丰供应链公司",
|
||||
"decision": "要求提供诉讼详情",
|
||||
"mitigation": "提供案件进展说明，评估财务影响<3%"
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"suggestion": "建议业务经理提供每起诉讼的详细情况（原告/被告、金额、进展），评估对财务的影响。",
|
||||
"smart_recommendation": {
|
||||
"primary_action": "提供诉讼清单（案由、金额、当前状态），说明对财务状况的影响评估",
|
||||
"alternative_actions": [
|
||||
"如为小额合同纠纷（<50万/起），提供说明后影响较小",
|
||||
"如为债务纠纷，需评估败诉风险和财务影响",
|
||||
"提供法律顾问意见书，说明诉讼风险可控"
|
||||
],
|
||||
"reference_case": {
|
||||
"case_id": "CAS-2025-08-203",
|
||||
"customer_name": "华泰建设工程",
|
||||
"scenario": "2 起小额合同纠纷，总金额<100万",
|
||||
"outcome": "确认为日常经营纠纷，不影响偿债能力，正常通过"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"level": "high",
|
||||
"title": "对外担保金额较大",
|
||||
"description": "远东新能源公交公司对外担保 3.5 亿元，为本次申请金额的 1.2 倍。",
|
||||
"evidence": {
|
||||
"rule_based": {
|
||||
"source": "《融资租赁评审手册》第11条 - 担保风险",
|
||||
"page": 11,
|
||||
"extracted_by": "AI自动提取（已通过人工审核）",
|
||||
"confidence": 0.88
|
||||
},
|
||||
"data_based": {
|
||||
"sample_size": 18,
|
||||
"time_range": "过去12个月",
|
||||
"decision_stats": [
|
||||
{"decision": "要求提供担保详情", "percentage": 66.7, "count": 12, "avg_processing_days": 5.8},
|
||||
{"decision": "降额通过", "percentage": 22.2, "count": 4, "avg_processing_days": 7.2},
|
||||
{"decision": "附加条件通过", "percentage": 11.1, "count": 2, "avg_processing_days": 6.5}
|
||||
],
|
||||
"similar_cases": [
|
||||
{
|
||||
"case_id": "CAS-2025-07-234",
|
||||
"customer_name": "华信集团",
|
||||
"decision": "附加条件通过",
|
||||
"mitigation": "提供被担保方财务报告，设置代偿预警机制"
|
||||
},
|
||||
{
|
||||
"case_id": "CAS-2025-09-045",
|
||||
"customer_name": "宏达投资公司",
|
||||
"decision": "降额通过（降20%）",
|
||||
"mitigation": "降低授信以控制担保风险敞口"
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"suggestion": "建议业务经理提供对外担保明细（被担保方、金额、期限），评估代偿风险。",
|
||||
"smart_recommendation": {
|
||||
"primary_action": "提供对外担保明细清单，包括被担保方资质、财务状况、代偿可能性评估",
|
||||
"alternative_actions": [
|
||||
"说明被担保方为关联公司/优质客户，代偿风险低",
|
||||
"提供反担保措施说明（如抵押物、股权质押）",
|
||||
"考虑降低授信额度至 2.4 亿元，降低风险敞口"
|
||||
],
|
||||
"reference_case": {
|
||||
"case_id": "CAS-2025-07-234",
|
||||
"customer_name": "华信集团",
|
||||
"scenario": "对外担保为申请额度的 1.2 倍",
|
||||
"outcome": "提供被担保方财务报告，设置代偿预警，附加条件通过"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"level": "medium",
|
||||
"title": "新能源行业政策依赖性",
|
||||
"description": "远东新能源公交公司属于新能源行业，收入可能依赖政府补贴，需关注补贴到位情况。",
|
||||
"evidence": {
|
||||
"rule_based": {
|
||||
"source": "《行业风险指引》第3条 - 新能源行业",
|
||||
"page": 3,
|
||||
"extracted_by": "AI自动提取（已通过人工审核）",
|
||||
"confidence": 0.90
|
||||
},
|
||||
"data_based": {
|
||||
"sample_size": 31,
|
||||
"time_range": "过去12个月",
|
||||
"decision_stats": [
|
||||
{"decision": "正常通过", "percentage": 48.4, "count": 15, "avg_processing_days": 4.5},
|
||||
{"decision": "要求补贴承诺函", "percentage": 38.7, "count": 12, "avg_processing_days": 6.2},
|
||||
{"decision": "附加条件通过", "percentage": 12.9, "count": 4, "avg_processing_days": 7.0}
|
||||
],
|
||||
"similar_cases": [
|
||||
{
|
||||
"case_id": "CAS-2025-08-112",
|
||||
"customer_name": "晨光新能源科技",
|
||||
"decision": "要求补贴承诺函",
|
||||
"mitigation": "地方政府出具补贴承诺函，补贴到位率>85%"
|
||||
},
|
||||
{
|
||||
"case_id": "CAS-2025-09-067",
|
||||
"customer_name": "绿动公交集团",
|
||||
"decision": "正常通过",
|
||||
"mitigation": "补贴延迟但现金流充足，运营收入稳定"
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"suggestion": "建议业务经理提供政府补贴承诺函、历史补贴到位情况，说明现金流不完全依赖补贴。",
|
||||
"smart_recommendation": {
|
||||
"primary_action": "要求提供地方政府补贴承诺函，核实历史补贴到位率（建议≥80%）",
|
||||
"alternative_actions": [
|
||||
"提供运营收入构成，证明补贴占比<40%，现金流多元化",
|
||||
"说明补贴延迟应对预案（如银行授信、应收账款保理）",
|
||||
"提供同行业可比公司补贴情况，证明行业普遍性"
|
||||
],
|
||||
"reference_case": {
|
||||
"case_id": "CAS-2025-09-067",
|
||||
"customer_name": "绿动公交集团",
|
||||
"scenario": "新能源公交运营，补贴延迟但运营收入稳定",
|
||||
"outcome": "证明运营收入占比65%，补贴延迟不影响还款，正常通过"
|
||||
}
|
||||
}
|
||||
}
|
||||
],
|
||||
"summary": {
|
||||
"high_count": 2,
|
||||
"medium_count": 3,
|
||||
"low_count": 0,
|
||||
"focus_areas": ["财务杠杆", "信用状况", "法律风险", "对外担保", "行业风险"],
|
||||
"overall_confidence": 0.86,
|
||||
"data_coverage": "99 个案例"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@router.get("/health")
|
||||
async def health_check():
|
||||
return {"status": "ok", "service": "风险研判助手（双轨驱动版）"}
|
||||
@@ -1,145 +0,0 @@
|
||||
"""Xingbang API — 兴邦金租评审工作流 + 自进化模块的 HTTP 接口。
|
||||
|
||||
端:
|
||||
POST /api/xingbang/workflow 运行五智能体审批流水线(返回全部产出)
|
||||
POST /api/xingbang/workflow/stream 流式运行(SSE, 逐步展示)
|
||||
GET /api/xingbang/evolution 查看自进化洞察
|
||||
GET /api/xingbang/trajectories 列出历史轨迹
|
||||
GET /api/xingbang/trajectories/{id} 读取单条轨迹
|
||||
|
||||
复用 mini-OpenClaw 的 AgentManager.llm 与后端基础设施。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
from fastapi import APIRouter
|
||||
from pydantic import BaseModel
|
||||
from sse_starlette.sse import EventSourceResponse
|
||||
|
||||
from graph.agent import agent_manager
|
||||
from xingbang.workflow import XingbangWorkflow
|
||||
from xingbang.config import XINGBANG_CONFIG
|
||||
|
||||
router = APIRouter(prefix="/api/xingbang", tags=["xingbang"])
|
||||
|
||||
|
||||
# 懒加载单例工作流(复用 agent_manager.llm)
|
||||
_workflow: XingbangWorkflow | None = None
|
||||
|
||||
|
||||
def _get_workflow() -> XingbangWorkflow:
|
||||
global _workflow
|
||||
if _workflow is None:
|
||||
if agent_manager._llm is None:
|
||||
# 若 agent 未初始化, 手动初始化(需要 BASE_DIR)
|
||||
from pathlib import Path as _P
|
||||
_workflow = XingbangWorkflow(
|
||||
llm=None,
|
||||
base_dir=_P(__file__).resolve().parent.parent,
|
||||
evolution_enabled=True,
|
||||
)
|
||||
raise RuntimeError("Agent 未初始化, 请先启动后端(会自动初始化 agent_manager)")
|
||||
_workflow = XingbangWorkflow(
|
||||
llm=agent_manager._llm,
|
||||
base_dir=Path(__file__).resolve().parent.parent,
|
||||
evolution_enabled=True,
|
||||
)
|
||||
return _workflow
|
||||
|
||||
|
||||
class WorkflowRequest(BaseModel):
|
||||
task: str # 客户/项目描述
|
||||
customer: str = "" # 客户名(用于轨迹标注)
|
||||
|
||||
|
||||
@router.get("/config")
|
||||
async def get_config():
|
||||
"""返回兴邦项目配置(数据源、五智能体、档位)。"""
|
||||
return XINGBANG_CONFIG
|
||||
|
||||
|
||||
@router.post("/workflow")
|
||||
async def run_workflow(req: WorkflowRequest):
|
||||
"""运行完整五智能体审批流水线。"""
|
||||
wf = _get_workflow()
|
||||
try:
|
||||
result = await wf.run(req.task, customer=req.customer)
|
||||
return result
|
||||
except RuntimeError as e:
|
||||
from fastapi import HTTPException
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.post("/workflow/stream")
|
||||
async def run_workflow_stream(req: WorkflowRequest):
|
||||
"""流式运行(SSE), 逐步展示五智能体进度与产出。"""
|
||||
wf = _get_workflow()
|
||||
|
||||
async def gen():
|
||||
async for event in wf.run_stream(req.task, customer=req.customer):
|
||||
yield {
|
||||
"event": event.get("event", "event"),
|
||||
"data": json.dumps(
|
||||
{k: v for k, v in event.items() if k != "event"},
|
||||
ensure_ascii=False,
|
||||
),
|
||||
}
|
||||
|
||||
return EventSourceResponse(gen())
|
||||
|
||||
|
||||
class FeedbackRequest(BaseModel):
|
||||
trajectory_id: str
|
||||
feedback: str # "positive" | "negative"
|
||||
|
||||
|
||||
@router.post("/evolution/feedback")
|
||||
async def submit_feedback(req: FeedbackRequest):
|
||||
"""提交用户反馈(Level 2 奖励信号), 追加进轨迹。"""
|
||||
try:
|
||||
traj_file = (
|
||||
Path(__file__).resolve().parent.parent
|
||||
/ "xingbang_evolution" / "trajectories" / f"{req.trajectory_id}.json"
|
||||
)
|
||||
if not traj_file.exists():
|
||||
return {"error": f"轨迹不存在: {req.trajectory_id}"}
|
||||
data = json.loads(traj_file.read_text(encoding="utf-8"))
|
||||
data.setdefault("user_feedback", req.feedback)
|
||||
data["user_feedback"] = req.feedback
|
||||
traj_file.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
|
||||
return {"status": "ok", "trajectory_id": req.trajectory_id, "feedback": req.feedback}
|
||||
except Exception as e:
|
||||
return {"error": str(e)}
|
||||
|
||||
|
||||
@router.get("/evolution")
|
||||
async def get_evolution():
|
||||
"""查看自进化洞察报告。"""
|
||||
wf = _get_workflow()
|
||||
report = wf.evolution.generate_insights()
|
||||
return {"insights": report, "config": XINGBANG_CONFIG}
|
||||
|
||||
|
||||
@router.get("/trajectories")
|
||||
async def list_trajectories():
|
||||
"""列出所有已保存轨迹。"""
|
||||
wf = _get_workflow()
|
||||
paths = wf.recorder.list_trajectories()
|
||||
return {"count": len(paths),
|
||||
"trajectories": [p.stem for p in paths]}
|
||||
|
||||
|
||||
@router.get("/trajectories/{trajectory_id}")
|
||||
async def get_trajectory(trajectory_id: str):
|
||||
"""读取单条轨迹详情。"""
|
||||
wf = _get_workflow()
|
||||
traj = wf.recorder.load(trajectory_id)
|
||||
if not traj:
|
||||
from fastapi import HTTPException
|
||||
raise HTTPException(status_code=404, detail="轨迹不存在")
|
||||
return traj
|
||||
@@ -0,0 +1,372 @@
|
||||
"""
|
||||
兴邦金租智能体系统 API 路由
|
||||
基于2026-08-18会议纪要真实痛点设计
|
||||
"""
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
from typing import Optional, Dict, Any
|
||||
import json
|
||||
import asyncio
|
||||
from pathlib import Path
|
||||
|
||||
from graph.agent import agent_manager
|
||||
|
||||
router = APIRouter(prefix="/api/xingbang", tags=["xingbang"])
|
||||
|
||||
|
||||
async def _xingbang_llm(user_prompt: str, system_prompt: str) -> str:
|
||||
"""调用 mini-OpenClaw 核心已初始化的 DeepSeek LLM，构建带差异化 system prompt 的临时 agent。
|
||||
|
||||
兼容核心 AgentManager：只复用其 LLM，不依赖不存在的 get_response 等方法。
|
||||
启用后可替换为本地模型(Qwen)以支持"数据不出域"。
|
||||
"""
|
||||
from langchain.agents import create_agent
|
||||
from langchain_core.messages import HumanMessage
|
||||
|
||||
if agent_manager._llm is None:
|
||||
from graph.agent import agent_manager as _am
|
||||
_am.initialize(Path(__file__).resolve().parent.parent)
|
||||
agent = create_agent(
|
||||
model=agent_manager._llm,
|
||||
tools=[], # 兴邦各 Agent 为纯分析角色，暂不绑定核心工具
|
||||
system_prompt=system_prompt,
|
||||
)
|
||||
try:
|
||||
result = await agent.ainvoke({"messages": [HumanMessage(content=user_prompt)]})
|
||||
msgs = result.get("messages", [])
|
||||
for m in reversed(msgs):
|
||||
if hasattr(m, "content") and m.type == "ai" and m.content:
|
||||
return m.content
|
||||
return str(result.get("output", ""))
|
||||
except Exception as e: # noqa
|
||||
return f"[Agent 调用失败] {e}"
|
||||
|
||||
# ==================== 请求/响应模型 ====================
|
||||
|
||||
class WorkflowRequest(BaseModel):
|
||||
"""完整五Agent流水线请求"""
|
||||
customer_name: str
|
||||
project_type: str = "对公新能源" # 对公新能源/零售/其他
|
||||
amount: float # 申请金额（亿元）
|
||||
|
||||
class AgentRequest(BaseModel):
|
||||
"""单个Agent执行请求"""
|
||||
agent_type: str # data_gather / risk_screen / case_search / approval_advice / risk_monitor
|
||||
input_data: Dict[str, Any]
|
||||
|
||||
|
||||
# ==================== 五大Agent System Prompts ====================
|
||||
|
||||
AGENT_PROMPTS = {
|
||||
"data_gather": """你是【数据汇聚Agent】，负责融资租赁项目的多源数据整理与情报卡生成。
|
||||
|
||||
**职责：**
|
||||
1. 从多源异构数据（财报PDF、工商信息、征信、中诚信评级模板、租赁物估值等）整理生成统一的"客户情报卡"
|
||||
2. 进行数据校验：交叉核对工商信息、财报数据、征信记录的一致性
|
||||
3. 标注风险标签：现金流压力、关联交易、对外担保、涉诉情况
|
||||
4. 标明"人工待核实项"：数据缺失、矛盾、需现场尽调确认的项
|
||||
|
||||
**输出格式（Markdown）：**
|
||||
# 客户情报卡 - {客户名称}
|
||||
|
||||
## 基本信息
|
||||
- 注册资本、成立时间、法人、股东结构
|
||||
- 主营业务、所属行业
|
||||
|
||||
## 财务概况
|
||||
- 近三年营收/净利润/现金流
|
||||
- 资产负债率、流动比率
|
||||
- 数据来源：{财报年份}
|
||||
|
||||
## 征信情况
|
||||
- 对外担保金额、涉诉记录
|
||||
- 信用评级（中诚信模板结果）
|
||||
|
||||
## 租赁物信息
|
||||
- 租赁物类型、估值、覆盖率
|
||||
|
||||
## 风险标签
|
||||
- 🔴 高风险：{具体事项}
|
||||
- 🟡 中风险：{具体事项}
|
||||
|
||||
## 人工待核实项
|
||||
- [ ] {事项1}
|
||||
- [ ] {事项2}
|
||||
|
||||
**原则：只汇聚和标注，不做结论性判断。**
|
||||
""",
|
||||
|
||||
"risk_screen": """你是【预审参谋Agent】，负责生成风险筛查清单。
|
||||
|
||||
**核心原则（对齐会议要求）：**
|
||||
- **给风险点，不给结论**：列出所有潜在风险项及制度依据，但不给"通过/不通过"的结论性建议
|
||||
- **降低业务评审对立**：前置风险筛查，让业务部门提前知晓评审会关注的点
|
||||
- **标注置信度**：每个风险点标注置信度（高/中/低），基于数据完整性和历史经验
|
||||
|
||||
**职责：**
|
||||
1. 基于"客户情报卡"，按公司评审手册逐项筛查风险点
|
||||
2. 引用制度条款和历史案例作为依据
|
||||
3. 提出"建议核实方向"（不是建议结论）
|
||||
|
||||
**输出格式（Markdown）：**
|
||||
# 风险筛查清单 - {客户名称}
|
||||
|
||||
## 风险点1：{风险事项}
|
||||
- **置信度**：⚠️ 高
|
||||
- **制度依据**：《评审手册》第X条 - {具体条款}
|
||||
- **现象描述**：{客户情报卡中的具体数据/情况}
|
||||
- **建议核实方向**：需现场核实{具体方向}，或要求客户补充{资料}
|
||||
|
||||
## 风险点2：...
|
||||
|
||||
## 汇总
|
||||
- 高风险项：{数量}
|
||||
- 中风险项：{数量}
|
||||
- 建议重点关注领域：{现金流/担保/租赁物合规/...}
|
||||
|
||||
**不要输出"建议通过/不通过"等结论性意见。**
|
||||
""",
|
||||
|
||||
"case_search": """你是【经验检索Agent】，负责从历史案例库中检索相似案例。
|
||||
|
||||
**职责：**
|
||||
1. 基于客户行业、规模、风险特征检索历史案例（成功+失败）
|
||||
2. 提取案例的关键决策依据和风险缓释措施
|
||||
3. 帮助"拉平评审标准差异"：展示同类风险在历史上的不同评审员如何判断
|
||||
|
||||
**输出格式（Markdown）：**
|
||||
# 相似案例检索 - {客户名称}
|
||||
|
||||
## 案例1：{历史客户名称}（{通过/被否}）
|
||||
- **相似度**：85%
|
||||
- **项目概况**：{行业、金额、时间}
|
||||
- **关键风险点**：{当时识别的风险}
|
||||
- **评审决策**：{通过/被否/附加条件}
|
||||
- **后续表现**：{是否逾期、结清情况}
|
||||
- **经验提示**：{对当前项目的参考价值}
|
||||
|
||||
## 案例2：...
|
||||
|
||||
## 经验总结
|
||||
- 同行业历史不良率：{%}
|
||||
- 关键风控措施：{担保增信/租赁物覆盖率/定期检查}
|
||||
|
||||
**目标：让评审员看到"过去怎么做的"，作为当前决策参考。**
|
||||
""",
|
||||
|
||||
"approval_advice": """你是【审批意见Agent】，负责生成标准化审批参考意见。
|
||||
|
||||
**职责：**
|
||||
1. 汇总前三个Agent（数据汇聚、风险筛查、经验检索）的产出
|
||||
2. 生成标准化审批参考文档，包含：建议结论、证据引用、风险缓释建议
|
||||
3. **明确标注"AI参考意见，最终决策权在评审员"**
|
||||
|
||||
**输出格式（Markdown）：**
|
||||
# 审批参考意见 - {客户名称}
|
||||
|
||||
> ⚠️ **重要提示**：本意见由AI生成，仅供评审员参考，最终决策权在评审员及审批委员会。评审员可一票否决。
|
||||
|
||||
## 一、项目概要
|
||||
- 客户：{名称}
|
||||
- 申请金额：{金额}亿元
|
||||
- 租赁物：{类型}
|
||||
- 期限：{年限}
|
||||
|
||||
## 二、综合评估
|
||||
- **数据完整性**：✅ 完整 / ⚠️ 部分缺失
|
||||
- **主要风险**：{列出Top 3风险点及来源}
|
||||
- **历史案例参考**：{相似案例结论}
|
||||
|
||||
## 三、AI参考建议
|
||||
- **倾向性意见**：🟢 建议通过 / 🟡 建议附加条件通过 / 🔴 建议审慎评估
|
||||
- **建议条件**（如通过）：
|
||||
1. {风险缓释措施1，如追加担保}
|
||||
2. {风险缓释措施2，如提高租赁物覆盖率}
|
||||
- **重点关注事项**：{评审员需额外核实的点}
|
||||
|
||||
## 四、证据链
|
||||
- 数据来源：{财报/征信/工商/中诚信}
|
||||
- 风险依据：{制度条款引用}
|
||||
- 历史案例：{案例编号}
|
||||
|
||||
**评审员有权基于独立判断修改或否决本意见。**
|
||||
""",
|
||||
|
||||
"risk_monitor": """你是【风险监控Agent】，负责审批空窗期与租后动态监控。
|
||||
|
||||
**职责：**
|
||||
1. 审批空窗期（立项→上会，约17工作日）：动态监控客户征信、涉诉、舆情变化
|
||||
2. 租后阶段：定期检查还款记录、保险覆盖、租赁物状态
|
||||
3. 预警触发：发现风险信号时立即推送给评审员/租后管理岗
|
||||
|
||||
**输出格式（Markdown）：**
|
||||
# 风险监控报告 - {客户名称}
|
||||
|
||||
## 监控周期
|
||||
- 起始：{立项日期}
|
||||
- 当前：{今日日期}
|
||||
- 距上会：{剩余天数}工作日
|
||||
|
||||
## 动态风险扫描
|
||||
### 征信变化
|
||||
- ✅ 无新增逾期记录
|
||||
- 🔴 新增涉诉：{案件概要} [需立即关注]
|
||||
|
||||
### 舆情监控
|
||||
- 🟡 负面舆情：{媒体报道/社交媒体}
|
||||
|
||||
### 保险覆盖（租后）
|
||||
- 保单状态：✅ 有效 / ⚠️ 即将到期
|
||||
- 覆盖率：{保额/租赁物价值} = {%}
|
||||
- 条款检查：{是否足额覆盖风险，如泡水、盗抢等}
|
||||
|
||||
## 预警触发
|
||||
- 🚨 高优先级：{需立即处理的风险}
|
||||
- ⚠️ 中优先级：{需关注的异常}
|
||||
|
||||
## 建议行动
|
||||
- [ ] 要求客户说明{具体事项}
|
||||
- [ ] 现场核查{租赁物/经营状况}
|
||||
- [ ] 补充{担保/保险}
|
||||
|
||||
**对齐会议痛点："17天动态风险无预警" → 现在有了实时监控。**
|
||||
"""
|
||||
}
|
||||
|
||||
|
||||
# ==================== 单Agent执行 ====================
|
||||
|
||||
async def execute_single_agent(agent_type: str, input_data: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""执行单个Agent"""
|
||||
if agent_type not in AGENT_PROMPTS:
|
||||
raise HTTPException(400, f"Unknown agent type: {agent_type}")
|
||||
|
||||
system_prompt = AGENT_PROMPTS[agent_type]
|
||||
user_prompt = f"""请基于以下输入数据执行任务：
|
||||
|
||||
{json.dumps(input_data, ensure_ascii=False, indent=2)}
|
||||
|
||||
严格按照你的角色职责和输出格式生成报告。"""
|
||||
|
||||
# 调用核心Agent（复用 mini-OpenClaw 的 agent_manager 及其 LLM）
|
||||
messages = [
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": user_prompt}
|
||||
]
|
||||
|
||||
# 复用 mini-OpenClaw 核心已初始化的 DeepSeek LLM，构建带差异化 system prompt 的临时 agent
|
||||
response = await _xingbang_llm(user_prompt, system_prompt)
|
||||
|
||||
return {
|
||||
"agent_type": agent_type,
|
||||
"output": response,
|
||||
"status": "completed"
|
||||
}
|
||||
|
||||
|
||||
# ==================== 完整流水线（SSE流式） ====================
|
||||
|
||||
async def run_workflow_stream(customer_name: str, project_type: str, amount: float):
|
||||
"""五Agent流水线 SSE流式执行"""
|
||||
|
||||
# 模拟数据包（实际应从数据库/文件读取）
|
||||
mock_data = {
|
||||
"customer_name": customer_name,
|
||||
"project_type": project_type,
|
||||
"amount": amount,
|
||||
"financial_data": {
|
||||
"revenue_2025": 15.2,
|
||||
"revenue_2024": 13.8,
|
||||
"revenue_2023": 12.1,
|
||||
"net_profit_2025": 1.8,
|
||||
"cash_flow_2025": 2.3,
|
||||
"debt_ratio": 0.62
|
||||
},
|
||||
"credit_info": {
|
||||
"external_guarantee": 3.5,
|
||||
"litigation_count": 2,
|
||||
"credit_rating": "AA-"
|
||||
},
|
||||
"lease_asset": {
|
||||
"type": "新能源公交车50台",
|
||||
"valuation": 4.2,
|
||||
"coverage_ratio": 1.4
|
||||
}
|
||||
}
|
||||
|
||||
# Agent执行顺序
|
||||
agents = [
|
||||
("data_gather", "数据汇聚"),
|
||||
("risk_screen", "预审参谋"),
|
||||
("case_search", "经验检索"),
|
||||
("approval_advice", "审批意见"),
|
||||
("risk_monitor", "风险监控")
|
||||
]
|
||||
|
||||
context = {"initial_data": mock_data}
|
||||
|
||||
for agent_type, agent_name in agents:
|
||||
# 发送agent_start事件
|
||||
yield f"event: agent_start\ndata: {json.dumps({'agent': agent_name, 'type': agent_type}, ensure_ascii=False)}\n\n"
|
||||
|
||||
await asyncio.sleep(0.5) # 模拟处理延迟
|
||||
|
||||
try:
|
||||
result = await execute_single_agent(agent_type, context)
|
||||
context[agent_type] = result["output"] # 传递给下一个Agent
|
||||
|
||||
# 发送agent_end事件
|
||||
yield f"event: agent_end\ndata: {json.dumps({'agent': agent_name, 'type': agent_type, 'output': result['output']}, ensure_ascii=False)}\n\n"
|
||||
|
||||
except Exception as e:
|
||||
yield f"event: error\ndata: {json.dumps({'agent': agent_name, 'error': str(e)}, ensure_ascii=False)}\n\n"
|
||||
break
|
||||
|
||||
# 完成
|
||||
yield f"event: done\ndata: {json.dumps({'status': 'completed'}, ensure_ascii=False)}\n\n"
|
||||
|
||||
|
||||
# ==================== API端点 ====================
|
||||
|
||||
@router.post("/workflow/stream")
|
||||
async def workflow_stream(req: WorkflowRequest):
|
||||
"""运行完整五Agent流水线（SSE）"""
|
||||
return StreamingResponse(
|
||||
run_workflow_stream(req.customer_name, req.project_type, req.amount),
|
||||
media_type="text/event-stream"
|
||||
)
|
||||
|
||||
|
||||
@router.post("/agent/execute")
|
||||
async def execute_agent(req: AgentRequest):
|
||||
"""执行单个Agent"""
|
||||
result = await execute_single_agent(req.agent_type, req.input_data)
|
||||
return result
|
||||
|
||||
|
||||
@router.get("/config")
|
||||
async def get_config():
|
||||
"""获取系统配置"""
|
||||
return {
|
||||
"agents": [
|
||||
{"id": "data_gather", "name": "数据汇聚Agent", "description": "多源数据整理生成情报卡"},
|
||||
{"id": "risk_screen", "name": "预审参谋Agent", "description": "给风险点不给结论，前置筛查"},
|
||||
{"id": "case_search", "name": "经验检索Agent", "description": "历史案例检索与经验复用"},
|
||||
{"id": "approval_advice", "name": "审批意见Agent", "description": "生成标准化审批参考意见"},
|
||||
{"id": "risk_monitor", "name": "风险监控Agent", "description": "审批空窗期+租后动态监控"}
|
||||
],
|
||||
"project_types": ["对公新能源", "对公传统", "零售乘用车", "零售二手车"],
|
||||
"model_config": {
|
||||
"provider": "DeepSeek",
|
||||
"model": "deepseek-v4-flash",
|
||||
"base_url": "http://49.232.133.151/v1"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@router.get("/health")
|
||||
async def health_check():
|
||||
"""健康检查"""
|
||||
return {"status": "ok", "service": "兴邦智能体系统"}
|
||||
@@ -0,0 +1,432 @@
|
||||
"""兴邦金租智能评审助手 - 统一API（7 个助手完整版）
|
||||
|
||||
基于 2026.8.18 会议痛点的完整解决方案：
|
||||
1. 立项前置风控助手 🔍 - 业务经理风险自查
|
||||
2. 中诚信智能填报助手 📊 - 激活十几万投资的评级模板
|
||||
3. 空窗期动态监控助手 🚨 - 17天空窗期风险重扫
|
||||
4. 保单条款合规核验助手 🛡️ - OCR+条款解析
|
||||
5. 评审报告辅助生成助手 📄 - 看资料+写报告提效
|
||||
6. 主审员智能分配助手 🎯 - 多维度负荷优化
|
||||
7. AI预审过滤+加速助手 🤖 - 团队经验预判+加速
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
from datetime import datetime
|
||||
from typing import AsyncGenerator, Dict, List, Optional
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
# 导入数据层
|
||||
from data_layer.erp_connector import get_erp_connector
|
||||
from data_layer.history_store import get_history_store
|
||||
from data_layer.reviewer_profile import get_reviewer_store
|
||||
from data_layer.team_experience import get_team_experience_store
|
||||
|
||||
router = APIRouter(prefix="/api/xingbang/unified", tags=["兴邦智能评审统一接口"])
|
||||
|
||||
|
||||
# ============ Pydantic 模型 ============
|
||||
|
||||
class ProjectBasicInfo(BaseModel):
|
||||
"""项目基础信息"""
|
||||
project_id: str = ""
|
||||
project_name: str
|
||||
client_name: str
|
||||
industry: str
|
||||
credit_amount: float # 万元
|
||||
lease_object: str = ""
|
||||
lease_value: float = 0 # 万元
|
||||
|
||||
|
||||
class FinancialData(BaseModel):
|
||||
"""财务数据"""
|
||||
registered_capital: float = 0
|
||||
established_years: int = 0
|
||||
asset_liability_ratio: float = 0
|
||||
current_ratio: float = 0
|
||||
quick_ratio: float = 0
|
||||
net_profit_2024: float = 0
|
||||
net_profit_2025: float = 0
|
||||
revenue_growth_rate: float = 0
|
||||
|
||||
|
||||
class CreditReport(BaseModel):
|
||||
"""征信报告"""
|
||||
overdue_count: int = 0
|
||||
query_count_recent_6m: int = 0
|
||||
credit_limit: float = 0
|
||||
enforcement_records: int = 0
|
||||
|
||||
|
||||
class InsurancePolicyData(BaseModel):
|
||||
"""保单数据"""
|
||||
policy_number: str
|
||||
insurance_company: str
|
||||
policy_type: str
|
||||
coverage_amount: float
|
||||
exclusions: List[str] = []
|
||||
policy_pdf_path: str = ""
|
||||
|
||||
|
||||
# ============ 助手 1：立项前置风控 ============
|
||||
|
||||
class Assistant1Request(BaseModel):
|
||||
"""立项前置风控请求"""
|
||||
project: ProjectBasicInfo
|
||||
financial: FinancialData
|
||||
credit: CreditReport
|
||||
|
||||
|
||||
@router.post("/assistant1/risk-check")
|
||||
async def assistant1_risk_check(request: Assistant1Request):
|
||||
"""助手1：立项前置风控自查（只给风险点，不给结论）"""
|
||||
|
||||
async def generate():
|
||||
try:
|
||||
# 获取团队经验
|
||||
team_exp = get_team_experience_store()
|
||||
thresholds = team_exp.get_approval_thresholds()
|
||||
risk_patterns = team_exp.get_risk_patterns(request.project.industry)
|
||||
red_flags = team_exp.get_industry_red_flags(request.project.industry)
|
||||
|
||||
yield f"data: {json.dumps({'type': 'start'}, ensure_ascii=False)}\n\n"
|
||||
|
||||
# 生成 Markdown 报告
|
||||
content = f"""# 立项前置风险自查清单
|
||||
|
||||
## 📋 项目基本信息
|
||||
- **项目名称**：{request.project.project_name}
|
||||
- **客户名称**：{request.project.client_name}
|
||||
- **行业**：{request.project.industry}
|
||||
- **授信金额**：{request.project.credit_amount} 万元
|
||||
- **租赁物**：{request.project.lease_object or '未填写'}
|
||||
- **租赁物价值**：{request.project.lease_value} 万元
|
||||
|
||||
---
|
||||
|
||||
## 🔍 风险自查结果
|
||||
|
||||
"""
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
|
||||
|
||||
# 检查高风险项
|
||||
high_risks = []
|
||||
medium_risks = []
|
||||
low_risks = []
|
||||
|
||||
# 1. 客户资质检查
|
||||
if request.financial.registered_capital < 1000:
|
||||
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))
|
||||
|
||||
if request.financial.established_years < 3:
|
||||
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))
|
||||
|
||||
# 2. 财务指标检查
|
||||
asset_liability = request.financial.asset_liability_ratio
|
||||
threshold_al = thresholds.get("资产负债率", {})
|
||||
|
||||
if asset_liability > threshold_al.get("critical", 0.8):
|
||||
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')}")
|
||||
elif asset_liability > threshold_al.get("warning", 0.7):
|
||||
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")
|
||||
else:
|
||||
low_risks.append(f"✅ **资产负债率**：{asset_liability:.1%}（良好）")
|
||||
|
||||
current_ratio = request.financial.current_ratio
|
||||
threshold_cr = thresholds.get("流动比率", {})
|
||||
|
||||
if current_ratio < threshold_cr.get("critical", 1.0):
|
||||
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')}")
|
||||
elif current_ratio < threshold_cr.get("warning", 1.2):
|
||||
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")
|
||||
else:
|
||||
low_risks.append(f"✅ **流动比率**：{current_ratio:.2f}（符合标准）")
|
||||
|
||||
# 3. 征信检查
|
||||
if request.credit.overdue_count > 0:
|
||||
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")
|
||||
else:
|
||||
low_risks.append("✅ **征信记录**：近 2 年无逾期（良好）")
|
||||
|
||||
if request.credit.enforcement_records > 0:
|
||||
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")
|
||||
else:
|
||||
low_risks.append("✅ **被执行记录**：无（良好）")
|
||||
|
||||
if request.credit.query_count_recent_6m > 10:
|
||||
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")
|
||||
|
||||
# 4. 租赁物检查
|
||||
if request.project.lease_value > 0:
|
||||
coverage_ratio = request.project.lease_value / request.project.credit_amount
|
||||
if coverage_ratio < 1.2:
|
||||
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")
|
||||
else:
|
||||
low_risks.append(f"✅ **租赁物覆盖率**：{coverage_ratio:.1%}（符合要求）")
|
||||
|
||||
# 5. 行业红线检查
|
||||
if red_flags:
|
||||
content_flags = f"\n### ⚠️ {request.project.industry} 行业常见风险点\n\n"
|
||||
for flag in red_flags:
|
||||
content_flags += f"- {flag}\n"
|
||||
content_flags += "\n**建议**：核实客户是否触及以上风险点\n\n"
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content_flags}, ensure_ascii=False)}\n\n"
|
||||
|
||||
# 输出风险项
|
||||
if high_risks:
|
||||
content_high = "### 🔴 高风险项（必须处理，否则评审大概率退回）\n\n"
|
||||
for i, risk in enumerate(high_risks, 1):
|
||||
content_high += f"{i}. {risk}\n\n"
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content_high}, ensure_ascii=False)}\n\n"
|
||||
|
||||
if medium_risks:
|
||||
content_medium = "### 🟡 中风险项（建议补充材料或说明）\n\n"
|
||||
for i, risk in enumerate(medium_risks, 1):
|
||||
content_medium += f"{i}. {risk}\n\n"
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content_medium}, ensure_ascii=False)}\n\n"
|
||||
|
||||
if low_risks:
|
||||
content_low = "### 🟢 低风险项（符合要求）\n\n"
|
||||
for risk in low_risks:
|
||||
content_low += f"- {risk}\n"
|
||||
content_low += "\n"
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content_low}, ensure_ascii=False)}\n\n"
|
||||
|
||||
# 整体评估
|
||||
if len(high_risks) == 0 and len(medium_risks) == 0:
|
||||
suggestion = "✅ **直接提交**：项目风险可控，可直接提交评审"
|
||||
elif len(high_risks) == 0:
|
||||
suggestion = "🟡 **补充材料后提交**：建议先处理中风险项，提高通过率"
|
||||
else:
|
||||
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"
|
||||
|
||||
content_final = f"""---
|
||||
|
||||
## 💡 整体评估
|
||||
|
||||
{suggestion}
|
||||
|
||||
**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。
|
||||
"""
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content_final}, 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")
|
||||
|
||||
|
||||
# ============ 助手 6：主审员智能分配 ============
|
||||
|
||||
class Assistant6Request(BaseModel):
|
||||
"""主审员智能分配请求"""
|
||||
project_industry: str
|
||||
project_amount: float # 万元
|
||||
project_complexity: int = Field(3, ge=1, le=5, description="项目复杂度 1-5")
|
||||
|
||||
|
||||
@router.post("/assistant6/allocate")
|
||||
async def assistant6_allocate(request: Assistant6Request):
|
||||
"""助手6：主审员智能分配（多维度评分）"""
|
||||
|
||||
try:
|
||||
reviewer_store = get_reviewer_store()
|
||||
|
||||
# 获取推荐列表
|
||||
recommendations = reviewer_store.get_recommended_reviewers(
|
||||
project_industry=request.project_industry,
|
||||
project_complexity=request.project_complexity,
|
||||
top_n=3
|
||||
)
|
||||
|
||||
# 获取所有主审员当前状态
|
||||
all_profiles = reviewer_store.get_all_profiles()
|
||||
reviewer_status = [
|
||||
{
|
||||
"name": name,
|
||||
"current_projects": profile["current_projects"],
|
||||
"specialty": profile["specialty"],
|
||||
"workload_capacity": profile["workload_capacity"],
|
||||
"status": "🔴 超载" if profile["current_projects"] >= profile["workload_capacity"]
|
||||
else ("🟡 偏高" if profile["current_projects"] >= profile["workload_capacity"] * 0.8 else "🟢 正常")
|
||||
}
|
||||
for name, profile in all_profiles.items()
|
||||
]
|
||||
|
||||
return {
|
||||
"reviewers": reviewer_status,
|
||||
"recommendations": recommendations,
|
||||
"project_info": {
|
||||
"industry": request.project_industry,
|
||||
"amount": request.project_amount,
|
||||
"complexity": request.project_complexity,
|
||||
},
|
||||
"algorithm_version": "v1.0_multidim_scoring",
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
# ============ 助手 7：AI预审过滤+加速 ============
|
||||
|
||||
class Assistant7Request(BaseModel):
|
||||
"""AI预审请求"""
|
||||
project: ProjectBasicInfo
|
||||
financial: FinancialData
|
||||
credit: CreditReport
|
||||
|
||||
|
||||
@router.post("/assistant7/pre-screen")
|
||||
async def assistant7_pre_screen(request: Assistant7Request):
|
||||
"""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）"""
|
||||
|
||||
async def generate():
|
||||
try:
|
||||
yield f"data: {json.dumps({'type': 'start'}, ensure_ascii=False)}\n\n"
|
||||
|
||||
# 获取团队经验和历史案例
|
||||
team_exp = get_team_experience_store()
|
||||
history_store = get_history_store()
|
||||
|
||||
thresholds = team_exp.get_approval_thresholds()
|
||||
rejection_reasons = team_exp.get_common_rejection_reasons(top_n=5)
|
||||
|
||||
# 相似案例检索
|
||||
similar_cases = history_store.search_similar_cases(
|
||||
industry=request.project.industry,
|
||||
credit_amount=request.project.credit_amount,
|
||||
limit=3
|
||||
)
|
||||
|
||||
content = f"""# AI预审报告（团队经验模式）
|
||||
|
||||
## 📊 项目信息
|
||||
- **项目名称**：{request.project.project_name}
|
||||
- **客户名称**：{request.project.client_name}
|
||||
- **行业**：{request.project.industry}
|
||||
- **授信金额**：{request.project.credit_amount} 万元
|
||||
|
||||
---
|
||||
|
||||
## 🤖 AI预审判断（基于团队 {team_exp.get_metadata().get('total_cases_analyzed', 0)} 个历史案例）
|
||||
|
||||
"""
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
|
||||
|
||||
# 快速红线检查
|
||||
red_line_hit = []
|
||||
warning_items = []
|
||||
|
||||
# 1. 财务红线
|
||||
if request.financial.asset_liability_ratio > thresholds.get("资产负债率", {}).get("critical", 0.8):
|
||||
red_line_hit.append("资产负债率超过红线")
|
||||
|
||||
if request.financial.current_ratio < thresholds.get("流动比率", {}).get("critical", 1.0):
|
||||
red_line_hit.append("流动比率低于红线")
|
||||
|
||||
# 2. 征信红线
|
||||
if request.credit.enforcement_records > 0:
|
||||
red_line_hit.append(f"存在 {request.credit.enforcement_records} 条被执行记录")
|
||||
|
||||
if request.credit.overdue_count > 2:
|
||||
red_line_hit.append(f"征信逾期次数过多（{request.credit.overdue_count} 次）")
|
||||
|
||||
# 3. 警告项
|
||||
if request.financial.revenue_growth_rate < 0:
|
||||
warning_items.append("营收负增长")
|
||||
|
||||
if request.credit.query_count_recent_6m > 10:
|
||||
warning_items.append("征信查询频繁")
|
||||
|
||||
# AI预审结论
|
||||
if red_line_hit:
|
||||
conclusion = "🔴 **不建议进入正式评审**"
|
||||
reason_text = "\n".join([f"- {item}" for item in red_line_hit])
|
||||
content_conclusion = f"""### {conclusion}
|
||||
|
||||
**触及红线项**：
|
||||
{reason_text}
|
||||
|
||||
**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。
|
||||
|
||||
"""
|
||||
elif len(warning_items) >= 2:
|
||||
conclusion = "🟡 **建议谨慎评审**"
|
||||
reason_text = "\n".join([f"- {item}" for item in warning_items])
|
||||
content_conclusion = f"""### {conclusion}
|
||||
|
||||
**警告项**：
|
||||
{reason_text}
|
||||
|
||||
**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。
|
||||
|
||||
"""
|
||||
else:
|
||||
conclusion = "🟢 **建议进入正式评审**"
|
||||
content_conclusion = f"""### {conclusion}
|
||||
|
||||
**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。
|
||||
|
||||
"""
|
||||
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content_conclusion}, ensure_ascii=False)}\n\n"
|
||||
|
||||
# 相似案例参考
|
||||
if similar_cases:
|
||||
content_cases = "\n---\n\n## 📚 相似案例参考\n\n"
|
||||
for i, case in enumerate(similar_cases, 1):
|
||||
result_emoji = "✅" if case.get("review_result") == "approved" else "❌"
|
||||
content_cases += f"""### 案例 {i}：{case.get('project_name', '未知项目')}
|
||||
- **行业**：{case.get('industry', '未知')}
|
||||
- **金额**：{case.get('credit_amount', 0)} 万元
|
||||
- **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()
|
||||
@@ -0,0 +1,569 @@
|
||||
"""兴邦金租智能评审助手 API v2 — 全新设计，推翻旧五智能体框架
|
||||
|
||||
核心痛点：
|
||||
1. 中诚信评级模板闲置（线下Excel手工录入）
|
||||
2. 保单条款覆盖度盲区（只看形式不看内容）
|
||||
3. 空窗期风险失控（17天立项到上会，期间风险恶化）
|
||||
4. 评审逻辑因人而异（同一事项30%/60%/90%都可能）
|
||||
5. 业务与评审对立（风险考量不一样）
|
||||
|
||||
新架构：4个专项助手
|
||||
- 立项前置风控助手：业务经理立项前风险自查（只给风险点不给结论）
|
||||
- 中诚信模板智能填报助手：激活闲置的中诚信模板，自动填充+评级
|
||||
- 空窗期动态监控助手：每3天重扫征信/涉诉/舆情，上会前强制重扫
|
||||
- 保单条款合规核验助手：OCR+条款解析，核验足额覆盖
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import AsyncGenerator
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = APIRouter(prefix="/api/xingbang/v2", tags=["兴邦智能评审助手V2"])
|
||||
|
||||
|
||||
# ============ Pydantic 模型 ============
|
||||
|
||||
class ProjectData(BaseModel):
|
||||
"""项目基础数据"""
|
||||
project_name: str
|
||||
client_name: str
|
||||
industry: str
|
||||
credit_amount: float # 授信金额（万元）
|
||||
lease_object: str # 租赁物
|
||||
lease_value: float # 租赁物价值（万元）
|
||||
financial_data: dict # 财务数据
|
||||
credit_report: dict # 征信报告
|
||||
litigation_records: list # 涉诉记录
|
||||
sentiment_info: dict # 舆情信息
|
||||
|
||||
|
||||
class InsurancePolicy(BaseModel):
|
||||
"""保单数据"""
|
||||
policy_number: str
|
||||
insurance_company: str
|
||||
coverage_amount: float # 保额（万元）
|
||||
policy_type: str # 险种
|
||||
exclusions: list[str] # 除外责任
|
||||
policy_pdf_path: str = ""
|
||||
|
||||
|
||||
class RiskCheckRequest(BaseModel):
|
||||
"""立项前置风控请求"""
|
||||
project_data: ProjectData
|
||||
|
||||
|
||||
class ZhongchengxinRequest(BaseModel):
|
||||
"""中诚信模板填报请求"""
|
||||
project_data: ProjectData
|
||||
|
||||
|
||||
class MonitoringRequest(BaseModel):
|
||||
"""空窗期监控请求"""
|
||||
project_id: str
|
||||
project_name: str
|
||||
client_name: str
|
||||
initial_data: ProjectData
|
||||
|
||||
|
||||
class PolicyCheckRequest(BaseModel):
|
||||
"""保单核验请求"""
|
||||
project_name: str
|
||||
client_name: str
|
||||
credit_amount: float
|
||||
lease_value: float
|
||||
policy: InsurancePolicy
|
||||
|
||||
|
||||
# ============ 辅助函数：创建专用 LLM 实例 ============
|
||||
|
||||
def _create_assistant_llm(system_prompt: str):
|
||||
"""创建专用助手 LLM（复用核心 DeepSeek 配置）"""
|
||||
import os
|
||||
from langchain_deepseek import ChatDeepSeek
|
||||
|
||||
return ChatDeepSeek(
|
||||
model=os.getenv("DEEPSEEK_MODEL", "deepseek-chat"),
|
||||
api_key=os.getenv("DEEPSEEK_API_KEY"),
|
||||
api_base=os.getenv("DEEPSEEK_BASE_URL", "https://api.deepseek.com"),
|
||||
temperature=0.3, # 降低温度，提高稳定性
|
||||
streaming=True,
|
||||
)
|
||||
|
||||
|
||||
# ============ 助手1：立项前置风控助手 ============
|
||||
|
||||
SYSTEM_PROMPT_RISK_CHECK = """你是兴邦金租的"立项前置风控助手"。
|
||||
|
||||
**你的职责**：
|
||||
帮助业务经理在立项前做风险自查，**只标识风险点，不给审批结论**，避免与评审员对立。
|
||||
|
||||
**工作流程**：
|
||||
1. 读取项目基础数据（客户、财务、征信、涉诉、舆情）
|
||||
2. 对照评审手册逐条自查
|
||||
3. 输出风险自查清单，标记：
|
||||
- 🔴 高风险：必须处理，否则评审大概率退回
|
||||
- 🟡 中风险：建议补充材料或说明
|
||||
- 🟢 低风险：符合要求，可直接提交
|
||||
|
||||
**评审手册核心要点**（简化版）：
|
||||
- 客户资质：注册资本≥1000万、成立时间≥3年、行业准入白名单
|
||||
- 财务指标：资产负债率≤70%、流动比率≥1.2、净利润连续两年为正
|
||||
- 征信记录：近2年无逾期、无被执行记录
|
||||
- 租赁物：价值必须≥授信金额×120%、符合适格性要求
|
||||
- 涉诉舆情：无重大诉讼、无负面舆情
|
||||
|
||||
**输出格式**（Markdown）：
|
||||
```markdown
|
||||
# 立项前置风险自查清单
|
||||
|
||||
## 项目基本信息
|
||||
- 项目名称：xxx
|
||||
- 客户名称：xxx
|
||||
- 授信金额：xxx万元
|
||||
|
||||
## 风险自查结果
|
||||
|
||||
### 🔴 高风险项（必须处理）
|
||||
1. [风险点] 具体描述 + 建议措施
|
||||
|
||||
### 🟡 中风险项（建议处理）
|
||||
1. [风险点] 具体描述 + 建议措施
|
||||
|
||||
### 🟢 低风险项（符合要求）
|
||||
1. [检查项] 符合标准
|
||||
|
||||
## 整体评估
|
||||
- 建议：[直接提交 / 补充材料后提交 / 重大调整后提交]
|
||||
```
|
||||
|
||||
**重要**：不要给"通过/不通过"结论，只客观列出风险点，让业务经理自己决策。
|
||||
"""
|
||||
|
||||
|
||||
async def _stream_risk_check(project_data: ProjectData) -> AsyncGenerator[str, None]:
|
||||
"""流式生成立项前置风控报告"""
|
||||
llm = _create_assistant_llm(SYSTEM_PROMPT_RISK_CHECK)
|
||||
|
||||
# 构造用户消息
|
||||
user_message = f"""请对以下项目进行立项前置风控自查：
|
||||
|
||||
**项目名称**：{project_data.project_name}
|
||||
**客户名称**：{project_data.client_name}
|
||||
**行业**：{project_data.industry}
|
||||
**授信金额**：{project_data.credit_amount}万元
|
||||
**租赁物**：{project_data.lease_object}
|
||||
**租赁物价值**：{project_data.lease_value}万元
|
||||
|
||||
**财务数据**：
|
||||
{json.dumps(project_data.financial_data, ensure_ascii=False, indent=2)}
|
||||
|
||||
**征信报告**：
|
||||
{json.dumps(project_data.credit_report, ensure_ascii=False, indent=2)}
|
||||
|
||||
**涉诉记录**：
|
||||
{json.dumps(project_data.litigation_records, ensure_ascii=False, indent=2)}
|
||||
|
||||
**舆情信息**：
|
||||
{json.dumps(project_data.sentiment_info, ensure_ascii=False, indent=2)}
|
||||
|
||||
请生成风险自查清单。
|
||||
"""
|
||||
|
||||
async for chunk in llm.astream(user_message):
|
||||
if hasattr(chunk, 'content'):
|
||||
yield chunk.content
|
||||
|
||||
|
||||
@router.post("/risk-check/stream")
|
||||
async def risk_check_stream(request: RiskCheckRequest):
|
||||
"""立项前置风控自查（流式返回）"""
|
||||
|
||||
async def event_generator():
|
||||
try:
|
||||
yield f"data: {json.dumps({'type': 'start', 'message': '正在分析项目风险...'}, ensure_ascii=False)}\n\n"
|
||||
|
||||
async for content in _stream_risk_check(request.project_data):
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
|
||||
|
||||
yield f"data: {json.dumps({'type': 'done', 'message': '风险自查完成'}, 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(event_generator(), media_type="text/event-stream")
|
||||
|
||||
|
||||
# ============ 助手2：中诚信模板智能填报助手 ============
|
||||
|
||||
SYSTEM_PROMPT_ZHONGCHENGXIN = """你是兴邦金租的"中诚信模板智能填报助手"。
|
||||
|
||||
**背景**：
|
||||
兴邦金租花了十几万咨询费购买中诚信评级模型（Excel模板），但因线下手工录入繁琐，一直闲置未用。
|
||||
|
||||
**你的职责**：
|
||||
1. 从项目数据自动提取关键指标
|
||||
2. 填充中诚信评级模板
|
||||
3. 计算评级结果（3A/2A/A/BBB/BB/B/C）
|
||||
4. 生成评级报告嵌入评审底稿
|
||||
|
||||
**中诚信评级模型简化版**（泛行业）：
|
||||
- 财务指标（40%）：资产负债率、流动比率、净资产收益率、营收增长率
|
||||
- 经营能力（30%）：行业地位、市场份额、客户集中度、盈利稳定性
|
||||
- 偿债能力（20%）：速动比率、利息保障倍数、现金流覆盖率
|
||||
- 发展前景（10%）：行业景气度、技术创新能力、政策支持
|
||||
|
||||
**评级标准**：
|
||||
- 3A（90-100分）：信用极好，违约风险极低
|
||||
- 2A（80-89分）：信用优良，违约风险很低
|
||||
- A（70-79分）：信用良好，违约风险较低
|
||||
- BBB（60-69分）：信用一般，违约风险中等
|
||||
- BB（50-59分）：信用较差，违约风险较高
|
||||
- B（40-49分）：信用差，违约风险高
|
||||
- C（<40分）：信用极差，违约风险极高
|
||||
|
||||
**输出格式**（Markdown）：
|
||||
```markdown
|
||||
# 中诚信评级报告
|
||||
|
||||
## 项目基本信息
|
||||
- 项目名称：xxx
|
||||
- 客户名称：xxx
|
||||
- 行业：xxx
|
||||
|
||||
## 评级指标填充
|
||||
|
||||
### 一、财务指标（40%）
|
||||
| 指标 | 数值 | 得分 |
|
||||
|------|------|------|
|
||||
| 资产负债率 | xx% | xx分 |
|
||||
| ... | ... | ... |
|
||||
**小计**：xx分
|
||||
|
||||
### 二、经营能力（30%）
|
||||
...
|
||||
|
||||
### 三、偿债能力（20%）
|
||||
...
|
||||
|
||||
### 四、发展前景（10%）
|
||||
...
|
||||
|
||||
## 评级结果
|
||||
- **综合得分**：xx分
|
||||
- **评级等级**：2A
|
||||
- **评级说明**：信用优良，违约风险很低
|
||||
|
||||
## 风险提示
|
||||
1. [关键风险点1]
|
||||
2. [关键风险点2]
|
||||
```
|
||||
"""
|
||||
|
||||
|
||||
async def _stream_zhongchengxin_report(project_data: ProjectData) -> AsyncGenerator[str, None]:
|
||||
"""流式生成中诚信评级报告"""
|
||||
llm = _create_assistant_llm(SYSTEM_PROMPT_ZHONGCHENGXIN)
|
||||
|
||||
user_message = f"""请为以下项目生成中诚信评级报告：
|
||||
|
||||
**项目名称**：{project_data.project_name}
|
||||
**客户名称**：{project_data.client_name}
|
||||
**行业**：{project_data.industry}
|
||||
**授信金额**：{project_data.credit_amount}万元
|
||||
|
||||
**财务数据**：
|
||||
{json.dumps(project_data.financial_data, ensure_ascii=False, indent=2)}
|
||||
|
||||
**征信报告**：
|
||||
{json.dumps(project_data.credit_report, ensure_ascii=False, indent=2)}
|
||||
|
||||
请填充中诚信评级模板并计算评级。
|
||||
"""
|
||||
|
||||
async for chunk in llm.astream(user_message):
|
||||
if hasattr(chunk, 'content'):
|
||||
yield chunk.content
|
||||
|
||||
|
||||
@router.post("/zhongchengxin/stream")
|
||||
async def zhongchengxin_stream(request: ZhongchengxinRequest):
|
||||
"""中诚信模板智能填报（流式返回）"""
|
||||
|
||||
async def event_generator():
|
||||
try:
|
||||
yield f"data: {json.dumps({'type': 'start', 'message': '正在填充中诚信评级模板...'}, ensure_ascii=False)}\n\n"
|
||||
|
||||
async for content in _stream_zhongchengxin_report(request.project_data):
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
|
||||
|
||||
yield f"data: {json.dumps({'type': 'done', 'message': '中诚信评级完成'}, 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(event_generator(), media_type="text/event-stream")
|
||||
|
||||
|
||||
# ============ 助手3：空窗期动态监控助手 ============
|
||||
|
||||
SYSTEM_PROMPT_MONITORING = """你是兴邦金租的"空窗期动态监控助手"。
|
||||
|
||||
**背景**：
|
||||
立项到上会需要17个工作日，期间客户征信/涉诉/舆情可能恶化，但无人重扫，导致上会时信息已过时。
|
||||
|
||||
**你的职责**：
|
||||
1. 对比初始数据与最新数据
|
||||
2. 识别异常变化（新增被执行、新增诉讼、舆情负面、信用卡逾期等）
|
||||
3. 评估风险等级（严重/一般/轻微）
|
||||
4. 生成红色预警报告
|
||||
|
||||
**监控维度**：
|
||||
- 征信变化：新增逾期、新增查询记录、信用卡额度变化
|
||||
- 涉诉变化：新增诉讼、新增被执行、执行金额变化
|
||||
- 舆情变化：负面新闻、行业风险、关联企业风险
|
||||
- 消费行为：淘宝消费骤降、信用卡逾期
|
||||
|
||||
**风险等级**：
|
||||
- 🔴 严重：新增被执行/重大诉讼/信用卡逾期，建议暂停审批
|
||||
- 🟡 一般：征信查询次数增多/轻微负面舆情，建议重点关注
|
||||
- 🟢 轻微：无明显异常
|
||||
|
||||
**输出格式**（Markdown）：
|
||||
```markdown
|
||||
# 空窗期动态监控报告
|
||||
|
||||
## 项目基本信息
|
||||
- 项目名称：xxx
|
||||
- 监控时间：xxx
|
||||
|
||||
## 异常变化检测
|
||||
|
||||
### 🔴 严重异常
|
||||
1. [异常项] 具体描述 + 建议措施
|
||||
|
||||
### 🟡 一般异常
|
||||
1. [异常项] 具体描述
|
||||
|
||||
### 🟢 无异常
|
||||
- 征信记录：无新增异常
|
||||
- 涉诉记录：无新增异常
|
||||
- 舆情信息：无新增负面
|
||||
|
||||
## 监控建议
|
||||
- [暂停审批 / 重点关注 / 正常推进]
|
||||
```
|
||||
"""
|
||||
|
||||
|
||||
async def _stream_monitoring_report(
|
||||
initial_data: ProjectData,
|
||||
latest_data: ProjectData
|
||||
) -> AsyncGenerator[str, None]:
|
||||
"""流式生成空窗期监控报告"""
|
||||
llm = _create_assistant_llm(SYSTEM_PROMPT_MONITORING)
|
||||
|
||||
user_message = f"""请对比以下项目的初始数据与最新数据，生成空窗期动态监控报告：
|
||||
|
||||
**项目名称**：{initial_data.project_name}
|
||||
**客户名称**：{initial_data.client_name}
|
||||
|
||||
**初始数据（立项时）**：
|
||||
征信报告：{json.dumps(initial_data.credit_report, ensure_ascii=False, indent=2)}
|
||||
涉诉记录：{json.dumps(initial_data.litigation_records, ensure_ascii=False, indent=2)}
|
||||
舆情信息：{json.dumps(initial_data.sentiment_info, ensure_ascii=False, indent=2)}
|
||||
|
||||
**最新数据（当前）**：
|
||||
征信报告：{json.dumps(latest_data.credit_report, ensure_ascii=False, indent=2)}
|
||||
涉诉记录：{json.dumps(latest_data.litigation_records, ensure_ascii=False, indent=2)}
|
||||
舆情信息：{json.dumps(latest_data.sentiment_info, ensure_ascii=False, indent=2)}
|
||||
|
||||
请识别异常变化并生成监控报告。
|
||||
"""
|
||||
|
||||
async for chunk in llm.astream(user_message):
|
||||
if hasattr(chunk, 'content'):
|
||||
yield chunk.content
|
||||
|
||||
|
||||
@router.post("/monitoring/stream")
|
||||
async def monitoring_stream(request: MonitoringRequest):
|
||||
"""空窗期动态监控（流式返回）
|
||||
|
||||
实际使用中，会定时调用此接口（每3天），传入最新数据
|
||||
这里为演示方便，模拟一次对比
|
||||
"""
|
||||
|
||||
# 模拟最新数据（实际应从外部数据源实时抓取）
|
||||
latest_data = request.initial_data.model_copy()
|
||||
latest_data.credit_report["overdue_count"] = latest_data.credit_report.get("overdue_count", 0) + 1
|
||||
latest_data.litigation_records.append({"case_number": "2026执1234", "amount": 50, "status": "执行中"})
|
||||
|
||||
async def event_generator():
|
||||
try:
|
||||
yield f"data: {json.dumps({'type': 'start', 'message': '正在对比数据变化...'}, ensure_ascii=False)}\n\n"
|
||||
|
||||
async for content in _stream_monitoring_report(request.initial_data, latest_data):
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
|
||||
|
||||
yield f"data: {json.dumps({'type': 'done', 'message': '监控完成'}, 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(event_generator(), media_type="text/event-stream")
|
||||
|
||||
|
||||
# ============ 助手4：保单条款合规核验助手 ============
|
||||
|
||||
SYSTEM_PROMPT_POLICY_CHECK = """你是兴邦金租的"保单条款合规核验助手"。
|
||||
|
||||
**背景**：
|
||||
兴邦金租要求客户为租赁物投保，保额需覆盖授信金额，但实际只检查"有没有保单"，不细看条款，导致出险时发现保单回不了。
|
||||
|
||||
**你的职责**：
|
||||
1. 解析保单关键信息（险种、保额、除外责任）
|
||||
2. 核验是否符合兴邦要求：
|
||||
- 保额 ≥ 授信金额（理想120%）
|
||||
- 险种必须包含：财产一切险/车辆损失险/盗抢险（根据租赁物类型）
|
||||
- 除外责任不能包含高频风险（如泡水、自然灾害等）
|
||||
3. 标记风险点
|
||||
4. 生成合规核验报告
|
||||
|
||||
**兴邦保单合规要求**：
|
||||
- 设备类：财产一切险/工程一切险，保额≥授信×120%
|
||||
- 车辆类：车损险+盗抢险+三者险，保额≥授信×120%
|
||||
- 除外责任禁止：战争、核辐射、故意损坏 OK，但泡水、自然灾害、机械故障等高频风险不能除外
|
||||
|
||||
**输出格式**（Markdown）：
|
||||
```markdown
|
||||
# 保单条款合规核验报告
|
||||
|
||||
## 保单基本信息
|
||||
- 保单号：xxx
|
||||
- 保险公司：xxx
|
||||
- 险种：xxx
|
||||
- 保额：xxx万元
|
||||
|
||||
## 合规核验结果
|
||||
|
||||
### ✅ 符合项
|
||||
1. [核验项] 符合要求
|
||||
|
||||
### ❌ 不符合项
|
||||
1. [核验项] 不符合要求 + 风险说明
|
||||
|
||||
## 核验结论
|
||||
- **是否合规**：[合规 / 不合规]
|
||||
- **风险等级**：[无风险 / 低风险 / 高风险]
|
||||
- **处理建议**：[通过 / 要求客户补正保单 / 拒绝]
|
||||
|
||||
## 详细说明
|
||||
[具体分析]
|
||||
```
|
||||
"""
|
||||
|
||||
|
||||
async def _stream_policy_check(
|
||||
project_name: str,
|
||||
client_name: str,
|
||||
credit_amount: float,
|
||||
lease_value: float,
|
||||
policy: InsurancePolicy
|
||||
) -> AsyncGenerator[str, None]:
|
||||
"""流式生成保单合规核验报告"""
|
||||
llm = _create_assistant_llm(SYSTEM_PROMPT_POLICY_CHECK)
|
||||
|
||||
required_coverage = credit_amount * 1.2 # 要求120%覆盖
|
||||
|
||||
user_message = f"""请核验以下保单是否符合兴邦金租要求：
|
||||
|
||||
**项目信息**：
|
||||
- 项目名称：{project_name}
|
||||
- 客户名称：{client_name}
|
||||
- 授信金额：{credit_amount}万元
|
||||
- 租赁物价值：{lease_value}万元
|
||||
- 要求保额：≥{required_coverage}万元（120%覆盖）
|
||||
|
||||
**保单信息**：
|
||||
- 保单号：{policy.policy_number}
|
||||
- 保险公司：{policy.insurance_company}
|
||||
- 保额：{policy.coverage_amount}万元
|
||||
- 险种：{policy.policy_type}
|
||||
- 除外责任：{json.dumps(policy.exclusions, ensure_ascii=False)}
|
||||
|
||||
请生成合规核验报告。
|
||||
"""
|
||||
|
||||
async for chunk in llm.astream(user_message):
|
||||
if hasattr(chunk, 'content'):
|
||||
yield chunk.content
|
||||
|
||||
|
||||
@router.post("/policy-check/stream")
|
||||
async def policy_check_stream(request: PolicyCheckRequest):
|
||||
"""保单条款合规核验（流式返回）"""
|
||||
|
||||
async def event_generator():
|
||||
try:
|
||||
yield f"data: {json.dumps({'type': 'start', 'message': '正在核验保单条款...'}, ensure_ascii=False)}\n\n"
|
||||
|
||||
async for content in _stream_policy_check(
|
||||
request.project_name,
|
||||
request.client_name,
|
||||
request.credit_amount,
|
||||
request.lease_value,
|
||||
request.policy
|
||||
):
|
||||
yield f"data: {json.dumps({'type': 'content', 'data': content}, ensure_ascii=False)}\n\n"
|
||||
|
||||
yield f"data: {json.dumps({'type': 'done', 'message': '保单核验完成'}, 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(event_generator(), media_type="text/event-stream")
|
||||
|
||||
|
||||
# ============ 综合工作台接口 ============
|
||||
|
||||
@router.get("/assistants/list")
|
||||
async def list_assistants():
|
||||
"""获取所有助手列表"""
|
||||
return {
|
||||
"assistants": [
|
||||
{
|
||||
"id": "risk-check",
|
||||
"name": "立项前置风控助手",
|
||||
"description": "业务经理立项前风险自查，只给风险点不给结论",
|
||||
"icon": "🔍",
|
||||
"pain_point": "业务与评审对立，项目被退回",
|
||||
"value": "降低退回率，缩短评审周期"
|
||||
},
|
||||
{
|
||||
"id": "zhongchengxin",
|
||||
"name": "中诚信模板智能填报助手",
|
||||
"description": "激活闲置的中诚信模板，自动填充+评级",
|
||||
"icon": "📊",
|
||||
"pain_point": "十几万的中诚信模板手工录入太繁琐",
|
||||
"value": "每个项目省30-60分钟，激活投资"
|
||||
},
|
||||
{
|
||||
"id": "monitoring",
|
||||
"name": "空窗期动态监控助手",
|
||||
"description": "每3天重扫征信/涉诉/舆情，上会前强制重扫",
|
||||
"icon": "🚨",
|
||||
"pain_point": "17天空窗期，上会时信息已过时",
|
||||
"value": "17天风险不落地，避免决策失误"
|
||||
},
|
||||
{
|
||||
"id": "policy-check",
|
||||
"name": "保单条款合规核验助手",
|
||||
"description": "OCR+条款解析，核验足额覆盖",
|
||||
"icon": "🛡️",
|
||||
"pain_point": "只看有没有保单，不看条款，出险回不了",
|
||||
"value": "避免保单风险盲区"
|
||||
}
|
||||
]
|
||||
}
|
||||
Reference in New Issue
Block a user