Update smart_breed_matcher.py

smart_breed_matcher.py

@@ -245,37 +245,6 @@ class SmartBreedMatcher:
         
         return similarity
 
-    # def _general_matching(self, description: str, top_n: int = 10) -> List[Dict]:
-    #     """基本的品種匹配邏輯"""
-    #     matches = []
-    #     for breed in self.dog_data:
-    #         breed_name = breed[1]
-    #         breed_description = breed[9]
-    #         temperament = breed[4]
-            
-    #         # 計算相似度
-    #         desc_embedding = self.model.encode(description)
-    #         breed_desc_embedding = self.model.encode(breed_description)
-    #         breed_temp_embedding = self.model.encode(temperament)
-            
-    #         # 計算描述和性格的相似度
-    #         desc_similarity = float(util.pytorch_cos_sim(desc_embedding, breed_desc_embedding))
-    #         temp_similarity = float(util.pytorch_cos_sim(desc_embedding, breed_temp_embedding))
-            
-    #         # 結合分數
-    #         final_score = (desc_similarity * 0.6 + temp_similarity * 0.4)
-            
-    #         matches.append({
-    #             'breed': breed_name,
-    #             'score': final_score,
-    #             'is_preferred': False,
-    #             'similarity': final_score,
-    #             'reason': "Matched based on general description and temperament"
-    #         })
-        
-    #     # 排序並返回前 N 個匹配結果
-    #     return sorted(matches, key=lambda x: -x['score'])[:top_n]
-
     def _general_matching(self, description: str, top_n: int = 10) -> List[Dict]:
         """基本的品種匹配邏輯，考慮描述、性格、噪音和健康因素"""
         matches = []