Update breed_recommendation.py

breed_recommendation.py

@@ -125,6 +125,63 @@ 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:
                 user_prefs = UserPreferences(
@@ -144,18 +201,27 @@ 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)
-
-                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]
-
+        
+                # 確保推薦結果不為空
+                if not recommendations:
+                    return gr.update(value="No matching breeds found. Please try adjusting your criteria.")
+        
+                # 創建完整的歷史記錄結果
+                history_results = []
+                for i, rec in enumerate(recommendations, 1):
+                    history_results.append({
+                        'breed': rec['breed'],
+                        'rank': i,  # 確保排名從1開始
+                        'overall_score': rec['final_score'],
+                        'base_score': rec['base_score'],
+                        'bonus_score': rec['bonus_score'],
+                        'scores': rec['scores'],
+                        'display_score': f"{rec['final_score']*100:.1f}%"  # 添加顯示用的分數
+                    })
+        
+                # 保存完整的搜索記錄
                 history_component.save_search(
                     user_preferences={
                         'living_space': args[0],
@@ -168,19 +234,12 @@ def create_recommendation_tab(UserPreferences, get_breed_recommendations, format
                         'has_children': args[7],
                         'children_age': args[8] if args[7] else None,
                         'noise_tolerance': args[9],
-                        'search_type': 'Criteria'  
+                        '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"
-                
+        
+                # 生成HTML結果
                 html_result = format_recommendation_html(recommendations, is_description_search=False)
                 enhanced_html = f"""
                     {html_result}
@@ -192,7 +251,7 @@ def create_recommendation_tab(UserPreferences, get_breed_recommendations, format
                 """
                 
                 return gr.update(value=enhanced_html)
-    
+        
             except Exception as e:
                 print(f"Error in find match: {str(e)}")
                 import traceback
@@ -200,23 +259,6 @@ def create_recommendation_tab(UserPreferences, get_breed_recommendations, format
                 return gr.update(value="Error getting recommendations")
            
 
-        # get_recommendations_btn.click(
-        #     fn=on_find_match_click,
-        #     inputs=[
-        #         living_space,
-        #         yard_access,        
-        #         exercise_time,
-        #         exercise_type,      
-        #         grooming_commitment,
-        #         experience_level,
-        #         time_availability, 
-        #         has_children,
-        #         children_age,
-        #         noise_tolerance
-        #     ],
-        #     outputs=recommendation_output
-        # )
-
         get_recommendations_btn.click(
             fn=on_find_match_click,
             inputs=[