mini-openclaw/backend/data_layer/team_experience.py

"""团队集体经验库

功能：
1. 学习团队历史评审行为（聚合，非个人）
2. 提取高频风险模式
3. 为预审助手提供经验支持
"""

import json
from typing import Dict, List, Optional
from pathlib import Path
from datetime import datetime
import logging

logger = logging.getLogger(__name__)


class TeamExperienceStore:
    """团队集体经验存储"""

    def __init__(self, data_dir: str = "./xingbang_data/team_experience"):
        self.data_dir = Path(data_dir)
        self.data_dir.mkdir(parents=True, exist_ok=True)
        self.experience_file = self.data_dir / "team_patterns.json"

        # 初始化默认经验模式
        if not self.experience_file.exists():
            self._init_default_patterns()

    def _init_default_patterns(self):
        """初始化默认团队经验模式"""
        default_patterns = {
            "risk_patterns": {
                "制造业": [
                    {
                        "risk_type": "应收账款集中度过高",
                        "frequency": 23,
                        "typical_threshold": "单一客户占比 > 30%",
                        "team_action": "要求补充第二担保人或增加保证金",
                    },
                    {
                        "risk_type": "原材料价格波动风险",
                        "frequency": 18,
                        "typical_threshold": "大宗商品占成本 > 50%",
                        "team_action": "要求提供价格锁定合同或套期保值证明",
                    },
                ],
                "新能源": [
                    {
                        "risk_type": "政策依赖度高",
                        "frequency": 34,
                        "typical_threshold": "补贴收入 > 营收 20%",
                        "team_action": "降低授信额度或缩短租赁期限",
                    },
                    {
                        "risk_type": "技术迭代淘汰风险",
                        "frequency": 21,
                        "typical_threshold": "设备技术落后 2 代以上",
                        "team_action": "要求租赁物残值担保或回购承诺",
                    },
                ],
                "交通运输": [
                    {
                        "risk_type": "油价波动影响",
                        "frequency": 15,
                        "typical_threshold": "燃油成本 > 营收 40%",
                        "team_action": "要求提供运价调整机制证明",
                    },
                ],
            },
            "approval_thresholds": {
                "资产负债率": {
                    "safe": 0.6,
                    "warning": 0.7,
                    "critical": 0.8,
                    "team_consensus": "≤60% 低风险，60-70% 中风险需补充说明，>70% 高风险需额外担保",
                },
                "流动比率": {
                    "safe": 1.5,
                    "warning": 1.2,
                    "critical": 1.0,
                    "team_consensus": "≥1.5 优秀，1.2-1.5 合格，<1.2 需关注短期偿债能力",
                },
                "净利润增长率": {
                    "safe": 0.15,
                    "warning": 0.05,
                    "critical": 0.0,
                    "team_consensus": "持续两年负增长通常不予通过",
                },
            },
            "industry_red_flags": {
                "光伏": ["产能严重过剩", "欧美双反调查", "地方政府欠补"],
                "房地产": ["三道红线踩线", "土地储备不足", "回款周期超18个月"],
                "餐饮": ["单店模型未跑通", "加盟商纠纷", "食品安全事故"],
            },
            "common_rejection_reasons": [
                {"reason": "担保方资产不足", "count": 45, "solution": "要求补充第二担保人"},
                {"reason": "征信查询次数过多", "count": 32, "solution": "要求客户说明查询原因"},
                {"reason": "涉诉金额过大", "count": 28, "solution": "等待诉讼结果或要求提供和解协议"},
                {"reason": "租赁物适格性存疑", "count": 25, "solution": "要求第三方评估报告"},
            ],
            "metadata": {
                "last_updated": datetime.now().isoformat(),
                "total_cases_analyzed": 156,
                "data_source": "2024-2025 年历史评审案例",
            },
        }

        with open(self.experience_file, "w", encoding="utf-8") as f:
            json.dump(default_patterns, f, ensure_ascii=False, indent=2)

        logger.info("团队经验模式初始化完成")

    def get_risk_patterns(self, industry: str = None) -> List[Dict]:
        """获取风险模式（可按行业过滤）"""
        with open(self.experience_file, "r", encoding="utf-8") as f:
            data = json.load(f)

        risk_patterns = data.get("risk_patterns", {})

        if industry:
            # 精确匹配或模糊匹配
            for key in risk_patterns:
                if industry in key or key in industry:
                    return risk_patterns[key]
            return []
        else:
            # 返回所有模式
            all_patterns = []
            for patterns in risk_patterns.values():
                all_patterns.extend(patterns)
            return all_patterns

    def get_approval_thresholds(self) -> Dict:
        """获取团队共识的审批阈值"""
        with open(self.experience_file, "r", encoding="utf-8") as f:
            data = json.load(f)

        return data.get("approval_thresholds", {})

    def get_industry_red_flags(self, industry: str) -> List[str]:
        """获取行业红线（团队总结的高危信号）"""
        with open(self.experience_file, "r", encoding="utf-8") as f:
            data = json.load(f)

        industry_flags = data.get("industry_red_flags", {})

        # 模糊匹配
        for key in industry_flags:
            if industry in key or key in industry:
                return industry_flags[key]

        return []

    def get_common_rejection_reasons(self, top_n: int = 10) -> List[Dict]:
        """获取高频退回原因及解决方案"""
        with open(self.experience_file, "r", encoding="utf-8") as f:
            data = json.load(f)

        reasons = data.get("common_rejection_reasons", [])
        return reasons[:top_n]

    def update_pattern(self, pattern_type: str, pattern_data: Dict):
        """更新经验模式（用于持续学习）"""
        with open(self.experience_file, "r", encoding="utf-8") as f:
            data = json.load(f)

        # 更新指定类型的模式
        if pattern_type in data:
            data[pattern_type].update(pattern_data)
            data["metadata"]["last_updated"] = datetime.now().isoformat()

            with open(self.experience_file, "w", encoding="utf-8") as f:
                json.dump(data, f, ensure_ascii=False, indent=2)

            logger.info(f"团队经验模式已更新: {pattern_type}")

    def get_metadata(self) -> Dict:
        """获取元数据"""
        with open(self.experience_file, "r", encoding="utf-8") as f:
            data = json.load(f)

        return data.get("metadata", {})


# 全局单例
_team_experience_store: Optional[TeamExperienceStore] = None


def get_team_experience_store() -> TeamExperienceStore:
    """获取团队经验存储单例"""
    global _team_experience_store
    if _team_experience_store is None:
        _team_experience_store = TeamExperienceStore()
    return _team_experience_store