good version for 算法注册

services/text-classification/ai_algorithm.py

@@ -0,0 +1,66 @@
+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}