From 290e4021811ca1eb218c48fb722b7ab9c88b68a5 Mon Sep 17 00:00:00 2001
From: xz2000 <xz20000522@163.com>
Date: Fri, 25 Jul 2025 13:55:31 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E9=A2=84=E6=B5=8B=E7=95=8C?=
 =?UTF-8?q?=E9=9D=A2=E4=B8=8D=E6=98=BE=E7=A4=BAbest=E7=89=88=E6=9C=AC?=
 =?UTF-8?q?=E5=92=8C=E4=B8=8D=E8=83=BD=E9=A2=84=E6=B5=8B?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../views/prediction/GlobalPredictionView.vue |   2 +-
 .../prediction/ProductPredictionView.vue      |   2 +-
 .../views/prediction/StorePredictionView.vue  |   2 +-
 prediction_history.db                         | Bin 167936 -> 167936 bytes
 server/api.py                                 |  28 ++++++++--
 server/predictors/model_predictor.py          |   5 ++
 server/utils/database_utils.py                |  48 +++++++++++++-----
 7 files changed, 67 insertions(+), 20 deletions(-)

diff --git a/UI/src/views/prediction/GlobalPredictionView.vue b/UI/src/views/prediction/GlobalPredictionView.vue
index 93c05a4..5f69a79 100644
--- a/UI/src/views/prediction/GlobalPredictionView.vue
+++ b/UI/src/views/prediction/GlobalPredictionView.vue
@@ -116,7 +116,7 @@ const filters = reactive({
 
 const pagination = reactive({
   currentPage: 1,
-  pageSize: 8
+  pageSize: 12
 })
 
 const filteredModelList = computed(() => {
diff --git a/UI/src/views/prediction/ProductPredictionView.vue b/UI/src/views/prediction/ProductPredictionView.vue
index 92b632d..0effe54 100644
--- a/UI/src/views/prediction/ProductPredictionView.vue
+++ b/UI/src/views/prediction/ProductPredictionView.vue
@@ -124,7 +124,7 @@ const filters = reactive({
 
 const pagination = reactive({
   currentPage: 1,
-  pageSize: 8
+  pageSize: 12
 })
 
 const filteredModelList = computed(() => {
diff --git a/UI/src/views/prediction/StorePredictionView.vue b/UI/src/views/prediction/StorePredictionView.vue
index e17179c..1dedee1 100644
--- a/UI/src/views/prediction/StorePredictionView.vue
+++ b/UI/src/views/prediction/StorePredictionView.vue
@@ -126,7 +126,7 @@ const filters = reactive({
 
 const pagination = reactive({
   currentPage: 1,
-  pageSize: 8
+  pageSize: 12
 })
 
 const filteredModelList = computed(() => {
diff --git a/prediction_history.db b/prediction_history.db
index ee8e5b01f0d658098f7a3cf4f6f1ccfafaf685ee..0f731fea210e658007544f29b1422bd99f350d34 100644
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diff --git a/server/api.py b/server/api.py
index dcd7db2..cd0a028 100644
--- a/server/api.py
+++ b/server/api.py
@@ -1329,10 +1329,17 @@ def predict():
         if not model_uid:
             return jsonify({"status": "error", "message": "缺少 'model_uid' 参数"}), 400
 
+        # 智能处理带 '_best' 后缀的UID，以解决前端key冲突问题 (兼容旧版Python)
+        is_best_request = model_uid.endswith('_best')
+        if is_best_request:
+            db_query_uid = model_uid[:-len('_best')]
+        else:
+            db_query_uid = model_uid
+
         # 从数据库查找模型记录
-        model_record = find_model_by_uid(model_uid)
+        model_record = find_model_by_uid(db_query_uid)
         if not model_record:
-            return jsonify({"status": "error", "message": f"模型UID '{model_uid}' 不存在"}), 404
+            return jsonify({"status": "error", "message": f"找不到基础模型UID '{db_query_uid}'"}), 404
 
         # 解析必要的模型元数据
         model_type = model_record.get('model_type')
@@ -1341,7 +1348,17 @@ def predict():
         
         # 解析 artifacts 找到模型文件路径
         artifacts = json.loads(model_record.get('artifacts', '{}'))
-        model_file_path = artifacts.get('best_model') or artifacts.get('versioned_model')
+        
+        # 根据请求类型选择正确的模型路径
+        if is_best_request:
+            model_file_path = artifacts.get('best_model')
+        else:
+            # 对于 v1, v2 等版本，使用 versioned_model
+            model_file_path = artifacts.get('versioned_model')
+        
+        # 如果特定版本路径不存在，提供一个后备方案，增加鲁棒性
+        if not model_file_path:
+            model_file_path = artifacts.get('best_model') or artifacts.get('versioned_model')
         
         # 修正路径问题：将相对路径转换为绝对路径以进行可靠的文件检查
         project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
@@ -1412,10 +1429,13 @@ def predict():
         analysis_result = prediction_result.get('analysis', {}) if prediction_result else {}
         metrics_result = analysis_result.get('metrics', {}) if analysis_result else {}
 
+        # 准备要保存到历史记录的model_type，确保与前端显示一致
+        history_model_type = f"{model_type}(best)" if is_best_request else model_type
+
         db_payload = {
             "prediction_uid": prediction_uid,
             "model_id": model_uid,
-            "model_type": model_type,
+            "model_type": history_model_type, # 使用处理后的一致性名称
             "product_name": product_name_to_save, # 使用修正后的名称
             "model_version": model_record.get('display_name'), # 将模型信息保存到新字段
             "prediction_scope": {"product_id": product_id, "store_id": store_id},
diff --git a/server/predictors/model_predictor.py b/server/predictors/model_predictor.py
index 2463543..c9aee19 100644
--- a/server/predictors/model_predictor.py
+++ b/server/predictors/model_predictor.py
@@ -86,6 +86,11 @@ register_predictor('default', default_pytorch_predictor)
 register_predictor('xgboost', default_pytorch_predictor)
 # 将新模型也注册给默认预测器
 register_predictor('cnn_bilstm_attention', default_pytorch_predictor)
+register_predictor('transformer', default_pytorch_predictor)
+register_predictor('mlstm', default_pytorch_predictor)
+register_predictor('kan', default_pytorch_predictor)
+register_predictor('optimized_kan', default_pytorch_predictor)
+register_predictor('tcn', default_pytorch_predictor)
 
 
 def load_model_and_predict(model_path: str, product_id: str, model_type: str, store_id: Optional[str] = None, future_days: int = 7, start_date: Optional[str] = None, analyze_result: bool = False, version: Optional[str] = None, training_mode: str = 'product', history_lookback_days: int = 30):
diff --git a/server/utils/database_utils.py b/server/utils/database_utils.py
index 764eb26..adde8a9 100644
--- a/server/utils/database_utils.py
+++ b/server/utils/database_utils.py
@@ -84,26 +84,48 @@ def query_models_from_db(filters: dict, page: int = 1, page_size: int = 10):
         if conditions:
             query += " WHERE " + " AND ".join(conditions)
             
-        # 获取总数
-        count_query = query.replace("*", "COUNT(*)")
-        cursor.execute(count_query, params)
-        total_count = cursor.fetchone()[0]
-        
-        # 添加分页
-        offset = (page - 1) * page_size
-        query += " ORDER BY created_at DESC LIMIT ? OFFSET ?"
-        params.extend([page_size, offset])
-        
+        # 修复分页逻辑：先查询所有符合条件的模型，再在内存中进行增强和分页
+        query += " ORDER BY created_at DESC"
         cursor.execute(query, params)
-        models = [dict(row) for row in cursor.fetchall()]
+        all_models = [dict(row) for row in cursor.fetchall()]
         
+        # 增强逻辑：如果模型同时有best版本，则额外生成一条记录
+        enhanced_models = []
+        for model in all_models:
+            # 首先添加原始的版本记录
+            enhanced_models.append(model)
+            
+            try:
+                artifacts = json.loads(model.get('artifacts', '{}'))
+                if artifacts and artifacts.get('best_model'):
+                    original_version = model.get('version', 'N/A')
+                    best_model_record = model.copy()
+                    best_model_record['version'] = f"best({original_version})"
+                    best_model_record['model_uid'] = f"{model['model_uid']}_best"
+                    best_model_record['model_type'] = f"{model['model_type']}(best)"
+                    
+                    new_artifacts = {
+                        'best_model': artifacts.get('best_model'),
+                        'scaler_X': artifacts.get('scaler_X'),
+                        'scaler_y': artifacts.get('scaler_y')
+                    }
+                    best_model_record['artifacts'] = json.dumps(new_artifacts)
+                    enhanced_models.append(best_model_record)
+            except (json.JSONDecodeError, TypeError):
+                continue
+        
+        # 在内存中进行分页
+        total_count = len(enhanced_models)
+        offset = (page - 1) * page_size
+        paginated_models = enhanced_models[offset : offset + page_size]
+
         return {
-            "models": models,
+            "models": paginated_models,
             "pagination": {
                 "total": total_count,
                 "page": page,
                 "page_size": page_size,
-                "total_pages": (total_count + page_size - 1) // page_size
+                "total_pages": (total_count + page_size - 1) // page_size if page_size > 0 else 0
             }
         }