# -*- coding: utf-8 -*-
"""
法务风控节点
审查维度：算法备案状态、实体清单命中、数据出境风险、知识产权诉讼
"""
import json
from .base_agent import BaseAgent


LAW_SYSTEM_PROMPT = """你是一名资深法务风控专家，精通以下法律法规：
- 《生成式人工智能服务管理暂行办法》
- 《互联网信息服务算法推荐管理规定》
- 《数据安全法》《个人信息保护法》
- 《出口管制法》及美国 BIS 实体清单相关规则
- 《科创板上市规则》中的合规要求

你的任务是基于提供的企业数据，从法律合规角度评估以下风险：
1. 算法备案合规风险：企业是否涉及AI业务但未完成算法备案
2. 地缘政治与出口管制风险：企业或其供应链是否受到制裁
3. 数据合规风险：是否存在数据出境、数据安全方面的隐患
4. 知识产权诉讼风险：是否面临重大IP纠纷

请以严谨的法律视角进行评估，输出JSON格式：
{
    "agent": "法务风控节点",
    "algo_compliance_risk": {"score": 0-100, "level": "高/中/低", "detail": "..."},
    "geopolitical_risk": {"score": 0-100, "level": "高/中/低", "detail": "..."},
    "data_compliance_risk": {"score": 0-100, "level": "高/中/低", "detail": "..."},
    "ip_litigation_risk": {"score": 0-100, "level": "高/中/低", "detail": "..."},
    "overall_law_risk": {"score": 0-100, "level": "高/中/低"},
    "key_findings": ["..."],
    "recommendations": ["..."]
}"""


class LawAgent(BaseAgent):
    """法务风控节点"""

    def __init__(self):
        super().__init__(
            name="法务风控节点",
            system_prompt=LAW_SYSTEM_PROMPT,
            role_icon="👩‍⚖️",
        )

    def evaluate(self, company_data: dict) -> dict:
        """执行法务风险评估"""
        prompt = self._build_prompt(company_data)
        result = self.infer_json(prompt)

        # 如果 JSON 解析失败，使用规则引擎
        if result.get("parse_error"):
            result = self._rule_based_evaluation(company_data)

        result["agent"] = "法务风控节点"
        result["icon"] = self.role_icon
        return result

    def _build_prompt(self, company_data: dict) -> str:
        """构建评估提示词"""
        return f"""请对以下科创企业进行法务风险评估：

企业名称：{company_data.get('short_name', company_data.get('company_name', '未知'))}
行业：{company_data.get('industry', '未知')}
领域：{company_data.get('sector', '未知')}

合规状态：
- 算法备案：{json.dumps(company_data.get('compliance', {}), ensure_ascii=False)}

供应链信息：
- 关键供应商：{json.dumps(company_data.get('supply_chain', {}).get('key_suppliers', []), ensure_ascii=False)}
- 供应商集中度风险：{company_data.get('supply_chain', {}).get('supplier_concentration_risk', '未知')}

技术路线：
{json.dumps(company_data.get('tech_route', {}), ensure_ascii=False)}

请输出严格的JSON评估结果。"""

    def fallback_inference(self, prompt: str) -> str:
        """规则引擎降级"""
        return json.dumps(self._rule_based_evaluation({}), ensure_ascii=False)

    def _rule_based_evaluation(self, company_data: dict) -> dict:
        """基于规则的法务风险评估"""
        compliance = company_data.get("compliance", {})
        supply_chain = company_data.get("supply_chain", {})
        sector = company_data.get("sector", "")

        # 算法备案风险
        algo_status = compliance.get("algo_filing_status", "")
        algo_score = 20
        algo_detail = "合规状态正常"
        if sector in ["AI", "软件", "互联网"] and algo_status == "不适用":
            algo_score = 60
            algo_detail = "涉及AI业务但标注为不适用，建议核实"
        elif "未" in algo_status or not algo_status:
            algo_score = 80
            algo_detail = "未查到算法备案记录，存在合规风险"
        elif "已备案" in algo_status:
            algo_score = 10
            algo_detail = "已完成算法备案"

        # 地缘政治风险
        entity_status = compliance.get("entity_list_status", "")
        geo_score = 15
        geo_detail = "未受出口管制影响"
        if "被列入" in entity_status:
            geo_score = 95
            geo_detail = f"已被列入实体清单: {compliance.get('sanctions_detail', '')}"
        elif supply_chain.get("supplier_concentration_risk") == "极高":
            geo_score = 70
            geo_detail = "核心供应链高度依赖海外，存在间接制裁风险"

        # 数据合规风险
        data_risk = compliance.get("data_export_risk", "低")
        data_score = {"高": 75, "中": 45, "低": 15}.get(data_risk, 20)
        data_detail = f"数据出境风险等级: {data_risk}"

        # 知识产权风险
        ip_score = 25
        ip_detail = "未发现重大IP纠纷"

        # 综合法务风险
        overall_score = int(
            algo_score * 0.25 + geo_score * 0.35 +
            data_score * 0.25 + ip_score * 0.15
        )

        return {
            "algo_compliance_risk": {"score": algo_score, "level": self._level(algo_score), "detail": algo_detail},
            "geopolitical_risk": {"score": geo_score, "level": self._level(geo_score), "detail": geo_detail},
            "data_compliance_risk": {"score": data_score, "level": self._level(data_score), "detail": data_detail},
            "ip_litigation_risk": {"score": ip_score, "level": self._level(ip_score), "detail": ip_detail},
            "overall_law_risk": {"score": overall_score, "level": self._level(overall_score)},
            "key_findings": [algo_detail, geo_detail, data_detail],
            "recommendations": ["建议定期审查合规状态", "关注实体清单更新动态"],
        }

    @staticmethod
    def _level(score: int) -> str:
        if score >= 70:
            return "高"
        elif score >= 40:
            return "中"
        return "低"