Update app.py

app.py

@@ -121,6 +121,7 @@ st.markdown(
 REPO_ID = "arabovs-ai-lab/PectinProductionModels"
 
 # Available models configuration
+# Available models configuration - ОБНОВЛЕННАЯ ВЕРСИЯ
 AVAILABLE_MODELS = {
     "best_model": {
         "subfolder": "best_model",
@@ -146,9 +147,39 @@ AVAILABLE_MODELS = {
         "subfolder": "linear_regression",
         "description": "📊 Linear Regression - базовая линейная модель",
         "color": "#FECA57"
+    },
+    # ДОБАВЛЕННЫЕ МОДЕЛИ
+    "extra_trees": {
+        "subfolder": "extra_trees",
+        "description": "🌳 Extra Trees - экстремальные случайные леса",
+        "color": "#FF9FF3"
+    },
+    "k_neighbors": {
+        "subfolder": "k-neighbors",
+        "description": "📏 K-Neighbors - метод ближайших соседей",
+        "color": "#54A0FF"
+    },
+    "lasso_regression": {
+        "subfolder": "lasso_regression",
+        "description": "🎯 Lasso Regression - L1-регуляризация",
+        "color": "#5F27CD"
+    },
+    "multilayer_perceptron": {
+        "subfolder": "multilayer_perceptron", 
+        "description": "🧠 Neural Network MLP - многослойный перцептрон",
+        "color": "#00D2D3"
+    },
+    "ridge_regression": {
+        "subfolder": "ridge_regression",
+        "description": "🏔️ Ridge Regression - L2-регуляризация", 
+        "color": "#FF9F43"
+    },
+    "support_vector_regression": {
+        "subfolder": "support_vector_regression",
+        "description": "🔗 Support Vector Regression - метод опорных векторов",
+        "color": "#A3CB38"
     }
 }
-
 # Sample types available
 SAMPLE_TYPES = ["ЯП(М)", "Абр.", "КрП", "Айв.", "Ткв", "Рв.", "ЯП(Ф)"]