Update breed_recommendation.py

breed_recommendation.py

@@ -125,68 +125,8 @@ def create_recommendation_tab(UserPreferences, get_breed_recommendations, format
                     elem_id="recommendation-output"  # 添加唯一ID以便追蹤
                 )
 
-        # def on_find_match_click(*args):
-        #     try:
-        #         user_prefs = UserPreferences(
-        #             living_space=args[0],
-        #             yard_access=args[1],       
-        #             exercise_time=args[2],
-        #             exercise_type=args[3],      
-        #             grooming_commitment=args[4],
-        #             experience_level=args[5],
-        #             time_availability=args[6],   
-        #             has_children=args[7],
-        #             children_age=args[8] if args[7] else None,
-        #             noise_tolerance=args[9],
-        #             space_for_play=True if args[0] != "apartment" else False,
-        #             other_pets=False,
-        #             climate="moderate",
-        #             health_sensitivity="medium",
-        #             barking_acceptance=args[9]
-        #         )
-
-        #         recommendations = get_breed_recommendations(user_prefs, top_n=10)
-
-        #         history_results = [{
-        #             'breed': rec['breed'],
-        #             'rank': rec['rank'],
-        #             'overall_score': rec['final_score'],
-        #             'base_score': rec['base_score'],
-        #             'bonus_score': rec['bonus_score'],
-        #             'scores': rec['scores']
-        #         } for rec in recommendations]
-
-        #         history_component.save_search(
-        #             user_preferences={
-        #                 'living_space': args[0],
-        #                 'yard_access': args[1],
-        #                 'exercise_time': args[2],
-        #                 'exercise_type': args[3],
-        #                 'grooming_commitment': args[4],
-        #                 'experience_level': args[5],
-        #                 'time_availability': args[6],
-        #                 'has_children': args[7],
-        #                 'children_age': args[8] if args[7] else None,
-        #                 'noise_tolerance': args[9],
-        #                 'search_type': 'Criteria'  
-        #             },
-        #             results=history_results
-        #         )
-
-        #         return format_recommendation_html(recommendations, is_description_search=False)
-
-        #     except Exception as e:
-        #         print(f"Error in find match: {str(e)}")
-        #         import traceback
-        #         print(traceback.format_exc())
-        #         return "Error getting recommendations"
-
         def on_find_match_click(*args):
             try:
-                # 時間處理
-                from datetime import datetime
-                import pytz
-                
                 user_prefs = UserPreferences(
                     living_space=args[0],
                     yard_access=args[1],       
@@ -204,28 +144,18 @@ def create_recommendation_tab(UserPreferences, get_breed_recommendations, format
                     health_sensitivity="medium",
                     barking_acceptance=args[9]
                 )
-        
+
                 recommendations = get_breed_recommendations(user_prefs, top_n=10)
-        
-                # 確保 recommendations 不為空
-                if not recommendations:
-                    return "No matching breeds found. Please adjust your criteria."
-        
-                # 創建標準化的結果列表
-                formatted_recommendations = []
-                for i, rec in enumerate(recommendations, 1):
-                    formatted_rec = {
-                        'breed': rec['breed'],
-                        'rank': i,
-                        'final_score': rec['final_score'],  # 直接使用，因為這是必需的
-                        'overall_score': rec['final_score'],  # 複製 final_score
-                        'base_score': rec.get('base_score', 0),
-                        'bonus_score': rec.get('bonus_score', 0),
-                        'scores': rec.get('scores', {})
-                    }
-                    formatted_recommendations.append(formatted_rec)
-                
-                # 使用相同的格式化數據來保存歷史記錄和生成 HTML
+
+                history_results = [{
+                    'breed': rec['breed'],
+                    'rank': rec['rank'],
+                    'overall_score': rec['final_score'],
+                    'base_score': rec['base_score'],
+                    'bonus_score': rec['bonus_score'],
+                    'scores': rec['scores']
+                } for rec in recommendations]
+
                 history_component.save_search(
                     user_preferences={
                         'living_space': args[0],
@@ -237,18 +167,19 @@ def create_recommendation_tab(UserPreferences, get_breed_recommendations, format
                         'time_availability': args[6],
                         'has_children': args[7],
                         'children_age': args[8] if args[7] else None,
-                        'noise_tolerance': args[9]
+                        'noise_tolerance': args[9],
+                        'search_type': 'Criteria'  
                     },
-                    results=formatted_recommendations  # 使用格式化後的結果
+                    results=history_results
                 )
-                
-                # 使用相同的格式化數據生成 HTML
-                return format_recommendation_html(formatted_recommendations, is_description_search=False)
-                
+
+                return format_recommendation_html(recommendations, is_description_search=False)
+
             except Exception as e:
-                print(f"Error details: {str(e)}")
+                print(f"Error in find match: {str(e)}")
+                import traceback
                 print(traceback.format_exc())
-                return f"Error getting recommendations: {str(e)}"
+                return "Error getting recommendations"
 
         get_recommendations_btn.click(
             fn=on_find_match_click,