Update smart_breed_matcher.py

smart_breed_matcher.py

@@ -245,6 +245,37 @@ 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 match_user_preference(self, description: str, top_n: int = 10) -> List[Dict]:
         """根據用戶描述匹配最適合的品種"""
         preferred_breed = self._detect_breed_preference(description)