import os

os.environ['HF_HUB_DISABLE_SYMLINKS_WARNING'] = '1'

from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity
import numpy as np


class TextSimilarityScorer:
    def __init__(self, model_name='shibing624/text2vec-base-chinese'):
        # 使用专门针对中文优化的模型
        self.model = SentenceTransformer(model_name)

    def calculate_similarity(self, standard_answer, student_answer):
        # 获取文本嵌入
        standard_embedding = self.model.encode([standard_answer])
        student_embedding = self.model.encode([student_answer])

        # 计算余弦相似度
        similarity = cosine_similarity(standard_embedding, student_embedding)[0][0]
        return similarity

    def score(self, standard_answer, student_answer, max_score=100):
        # 基础相似度
        similarity = self.calculate_similarity(standard_answer, student_answer)

        # 长度比例
        len_ratio = min(len(student_answer) / len(standard_answer), 1.0)

        # 关键词覆盖度（简单实现）
        standard_keywords = set(standard_answer.split())
        student_keywords = set(student_answer.split())
        keyword_coverage = len(student_keywords.intersection(standard_keywords)) / len(standard_keywords)

        # 综合评分
        final_score = (
                              similarity * 0.6 +  # 语义相似度权重
                              len_ratio * 0.2 +  # 长度比例权重
                              keyword_coverage * 0.2  # 关键词覆盖权重
                      ) * max_score

        return round(final_score)


# 使用示例
def main():
    # 初始化评分器
    scorer = TextSimilarityScorer()

    # 示例标准答案和学生答案
    standard_answer = "机器学习是人工智能的一个子领域，它使用统计学方法让计算机系统能够从数据中学习和改进。"
    student_answers = [
        "机器学习是AI的分支，通过统计方法让计算机从数据中学习。",  # 相似但较简短
        "机器学习是计算机科学的一个领域，使用统计方法从数据中学习模式。",  # 比较相似
        "人工智能是计算机科学的重要领域。",
        "哈哈哈哈哈哈哈哈。"# 不太相关
    ]

    # 对每个学生答案进行评分
    for i, student_answer in enumerate(student_answers, 1):
        similarity = scorer.calculate_similarity(standard_answer, student_answer)
        score = scorer.score(standard_answer, student_answer)
        print(f"\n学生答案 {i}:")
        print(f"答案: {student_answer}")
        print(f"相似度: {similarity:.2f}")
        print(f"得分: {score}")


if __name__ == "__main__":
    main()