修复遗留合并BUG

api/app/repositories/neo4j/graph_search.py

@@ -305,11 +305,18 @@ async def search_graph(
             results[key] = _deduplicate_results(results[key])
     
     # 更新知识节点的激活值（Statement, ExtractedEntity, MemorySummary）
-    results = await _update_search_results_activation(
-        connector=connector,
-        results=results,
-        end_user_id=end_user_id
+    # Skip activation updates if only searching summaries (optimization)
+    needs_activation_update = any(
+        key in include and key in results and results[key]
+        for key in ['statements', 'entities', 'chunks']
     )
+
+    if needs_activation_update:
+        results = await _update_search_results_activation(
+            connector=connector,
+            results=results,
+            end_user_id=end_user_id
+        )
     
     return results
 
@@ -417,14 +424,23 @@ async def search_graph_by_embedding(
             results[key] = _deduplicate_results(results[key])
 
     # 更新知识节点的激活值（Statement, ExtractedEntity, MemorySummary）
-    update_start = time.time()
-    results = await _update_search_results_activation(
-        connector=connector,
-        results=results,
-        end_user_id=end_user_id
+    # Skip activation updates if only searching summaries (optimization)
+    needs_activation_update = any(
+        key in include and key in results and results[key]
+        for key in ['statements', 'entities', 'chunks']
     )
-    update_time = time.time() - update_start
-    print(f"[PERF] Activation value updates took: {update_time:.4f}s")
+
+    if needs_activation_update:
+        update_start = time.time()
+        results = await _update_search_results_activation(
+            connector=connector,
+            results=results,
+            end_user_id=end_user_id
+        )
+        update_time = time.time() - update_start
+        logger.info(f"[PERF] Activation value updates took: {update_time:.4f}s")
+    else:
+        logger.info(f"[PERF] Skipping activation updates (only summaries)")
 
     return results
 async def get_dedup_candidates_for_entities(  # 适配新版查询：使用全文索引按名称检索候选实体

api/app/services/emotion_analytics_service.py

@@ -505,7 +505,7 @@ class EmotionAnalyticsService:
                     )
                     config_service = MemoryConfigService(db)
                     memory_config = config_service.load_memory_config(
-                        config_id=int(config_id),
+                        config_id=(config_id),
                         service_name="EmotionAnalyticsService.generate_emotion_suggestions"
                     )
                     from app.core.memory.utils.llm.llm_utils import MemoryClientFactory

api/app/services/memory_config_service.py

@@ -61,7 +61,7 @@ def _validate_config_id(config_id):
         
         # Fall back to integer parsing
         try:
-            parsed_id = int(config_id_stripped)
+            parsed_id = config_id_stripped
             if parsed_id <= 0:
                 raise InvalidConfigError(
                     f"Configuration ID must be positive: {parsed_id}",

api/app/services/memory_perceptual_service.py

@@ -92,17 +92,15 @@ class MemoryPerceptualService:
 
             result = {
                 "id": str(memory.id),
-                "perceptual_type": perceptual_type,
                 "file_name": memory.file_name,
                 "file_path": memory.file_path,
-                "file_ext": memory.file_ext,
-                "storage_service": memory.storage_service,  
-                "meta_data": memory.meta_data,
+                "storage_type": memory.storage_service,
                 "summary": memory.summary,
                 "keywords": content.keywords,
                 "topic": content.topic,
                 "domain": content.domain,
                 "created_time": int(memory.created_time.timestamp()*1000),
+                **detail
             }
 
             business_logger.info(