import logging
from typing import List, Dict, Any

logger = logging.getLogger(__name__)


class TextClassifier:
    """文本分类器"""
    
    def __init__(self):
        """初始化文本分类器"""
        logger.info("初始化文本分类器")
        # 这里可以加载预训练模型
        # 示例中使用简单的规则分类
    
    def classify(self, texts: List[str], params: Dict[str, Any] = None) -> List[Dict[str, Any]]:
        """分类文本
        
        Args:
            texts: 文本列表
            params: 分类参数
            
        Returns:
            分类结果列表
        """
        if params is None:
            params = {}
        
        threshold = params.get("threshold", 0.5)
        
        results = []
        for text in texts:
            # 简单的规则分类示例
            classification = self._simple_classify(text)
            results.append({
                "text": text,
                "label": classification["label"],
                "confidence": classification["confidence"]
            })
        
        return results
    
    def _simple_classify(self, text: str) -> Dict[str, Any]:
        """简单的文本分类实现
        
        Args:
            text: 待分类的文本
            
        Returns:
            分类结果
        """
        # 简单的规则分类
        text_lower = text.lower()
        
        if any(keyword in text_lower for keyword in ["技术", "科技", "编程", "代码"]):
            return {"label": "技术", "confidence": 0.9}
        elif any(keyword in text_lower for keyword in ["体育", "足球", "篮球", "运动"]):
            return {"label": "体育", "confidence": 0.85}
        elif any(keyword in text_lower for keyword in ["电影", "音乐", "娱乐", "游戏"]):
            return {"label": "娱乐", "confidence": 0.8}
        elif any(keyword in text_lower for keyword in ["美食", "餐厅", "烹饪", "食物"]):
            return {"label": "美食", "confidence": 0.85}
        elif any(keyword in text_lower for keyword in ["政治", "新闻", "政府", "政策"]):
            return {"label": "政治", "confidence": 0.9}
        else:
            return {"label": "其他", "confidence": 0.7}
