AI法律应用：Lexis与DoNotPay怎么用

"""AI法律检索核心流程示例演示如何用NLP和向量检索实现法律案例智能检索"""from dataclasses import dataclass, fieldfrom typing import Listimport math @dataclassclass LegalCase:    """法律判例数据结构"""    case_id: str    title: str    facts: str           # 案件事实    legal_basis: list     # 引用法条    court: str           # 审理法院    year: int            # 判决年份    outcome: str         # 判决结果    embedding: list = field(default_factory=list)  # 向量嵌入 class LegalSearchEngine:    """AI法律检索引擎"""    def __init__(self):        self.cases: List[LegalCase] = []     def add_case(self, case: LegalCase):        self.cases.append(case)     def cosine_similarity(self, vec_a: list, vec_b: list) -> float:        """计算两个向量的余弦相似度"""        dot_product = sum(a * b for a, b in zip(vec_a, vec_b))        norm_a = math.sqrt(sum(a * a for a in vec_a))        norm_b = math.sqrt(sum(b * b for b in vec_b))        if norm_a == 0 or norm_b == 0:            return 0.0        return dot_product / (norm_a * norm_b)     def search_similar_cases(self, query_embedding: list,                              top_k: int = 5) -> list:        """检索最相似的法律案例"""        scored = []        for case in self.cases:            if case.embedding:                score = self.cosine_similarity(query_embedding,                                                case.embedding)                scored.append((case, score))        scored.sort(key=lambda x: x[1], reverse=True)        return scored[:top_k]     def recommend_legal_basis(self, case_facts: str) -> list:        """根据案件事实推荐相关法条"""        # 实际应用中由NLP模型完成        keyword_rules = {            "合同": ["民法典第464条", "民法典第577条"],            "劳动": ["劳动法第3条", "劳动合同法第10条"],            "侵权": ["民法典第1165条", "民法典第1179条"],        }        results = []        for keyword, laws in keyword_rules.items():            if keyword in case_facts:                results.extend(laws)        return results # 使用示例engine = LegalSearchEngine()# 添加示例案例engine.add_case(LegalCase(    case_id="2023-H001",    title="某合同纠纷案",    facts="被告未按合同约定时间交付货物，构成违约",    legal_basis=["民法典第577条"],    court="北京市海淀区人民法院",    year=2023,    outcome="原告胜诉，被告赔偿违约金"))# 推荐相关法条basis = engine.recommend_legal_basis("合同违约赔偿纠纷")print(f"推荐法条: {basis}")