改成雙層config架構,調整app處理config資料, 增加inno setup的iss file, auto renew global config

README.md

@@ -1,26 +1,7 @@
-<!-- main page 
+# Kneron Academy v2.0
-1. -> example (python code) -> 讀 folder 檔案 -> 選
+這個應用程式是一個基於 Python、PyQt5、OpenCV 以及 Kneron SDK（kp）開發的 AI 應用 APP，使用者可以透過鏡頭、麥克風或上傳的方式經由 Kneron NPU 裝置進行實時運算。
--> 抓 camera -> -i image -m model
-2. run code -->
 
 
-
-<!-- config for python script 需要有以下的資料:
-1. function name to display
-2. script name
-3. device availibility (considering if the script name doesn't consist dongle type)
-4. model's name
-5. input information (frames, images, voice etc.)
-6. input parameters
-7. output parameters -->
-
-
-# Innovedus AI Playground
-
-這個應用程式是一個 AI Playground，用於通過相機鏡頭或使用者上傳圖片進行推論（例如火災檢測）。應用程式基於 Python、PyQt5、OpenCV 以及 Kneron SDK（kp）開發，支援 Video 模式與 Image 模式。
-
----
-
 ## 目錄
 - [安裝設定](#安裝設定)
 - [專案架構](#專案架構)
@@ -74,8 +55,9 @@ project/
 upload/
     └── photos, videos, or mp3 files
 utils/
-    └── plugins/
+    ├── config.json
-        ├── mode1/
+    ├── REAMDE.md
+    │── mode1/
     │   ├── model1/
     │   │   ├── script.py
     │   │   ├── model_file(s)
@@ -93,19 +75,17 @@ utils/
             ├── script.py
             ├── model_file(s)
             └── config.json
-    └──firmware\
+firmware\
     ├── KLXXX/
     │   ├── fw_scpu.bin
     │   ├── fw_ncpu.bin
     │   ├── VERSION
     │   └── other files
-         ├── KLXXX/
+    └── KLXXX/
         ├── fw_scpu.bin
         ├── fw_ncpu.bin
         ├── VERSION
         └── other files
-    └──config.json
-    └──REAMDE.md
 ```
 ## 功能概述
 
@@ -164,3 +144,69 @@ pyinstaller --onefile --windowed main.py --additional-hooks-dir=hooks --add-data
 
 ## APP資料加密
 目前預計使用 [pyarmor](https://github.com/dashingsoft/pyarmor) 進行加密
+
+
+## Script & Model 的設定
+整個 utils folder 會分成兩層: global config 和 model config
+
+model config 範例如下
+``` json
+{
+  "display_name": "人臉偵測 (ResNet-18)",
+  "description": "使用ResNet-18架構的高精度人臉偵測模型，可即時標記影像中的人臉位置",
+  "model_file": "face_detection.nef",
+  "input_info": {
+    "type": "video",
+    "supported_formats": ["mp4", "avi", "webm"]
+  },
+  "input_parameters": {
+    "threshold": 0.75,
+    "max_faces": 10,
+    "tracking": true
+  },
+  "compatible_devices": ["KL520", "KL720"]
+}
+```
+global config 範例如下
+```json
+{
+  "plugins": [
+    {
+      "mode": "face_recognition",
+      "display_name": "人臉辨識",
+      "models": [
+        {
+          "name": "face_detection",
+          "display_name": "人臉偵測 (ResNet-18)",
+          "description": "基於ResNet-18的高精度人臉偵測",
+          "compatible_devices": ["KL520", "KL720"]
+        },
+        {
+          "name": "age_gender",
+          "display_name": "年齡性別辨識 (VGG-Face)",
+          "description": "使用VGG-Face架構辨識人臉年齡與性別",
+          "compatible_devices": ["KL520", "KL720"]
+        }
+      ]
+    },
+    {
+      "mode": "object_detection",
+      "display_name": "物體偵測",
+      "models": [
+        {
+          "name": "yolo_v5",
+          "display_name": "物體偵測 (YOLOv5)",
+          "description": "使用YOLOv5進行實時物體偵測與分類",
+          "compatible_devices": ["KL720"]
+        },
+        {
+          "name": "rcnn",
+          "display_name": "精確物體識別 (Faster R-CNN)",
+          "description": "以Faster R-CNN為基礎的高精度物體識別",
+          "compatible_devices": ["KL720"]
+        }
+      ]
+    }
+  ]
+}
+```

dist/test.iss

@@ -1,12 +1,10 @@
 ; Script generated by the Inno Setup Script Wizard.
 ; SEE THE DOCUMENTATION FOR DETAILS ON CREATING INNO SETUP SCRIPT FILES!
-
 #define MyAppName "Kneron Academy"
 #define MyAppVersion "2.0"
 #define MyAppPublisher "Innovedus Inc."
 #define MyAppURL "https://www.example.com/"
 #define MyAppExeName "main.exe"
-
 [Setup]
 ; 唯一的 AppId，請勿在其他應用程式中重複使用
 AppId={{0894596D-D78B-4D8C-97CC-D90FE98E26E0}}
@@ -28,37 +26,34 @@ PrivilegesRequired=lowest
 OutputBaseFilename=mysetup
 SolidCompression=yes
 WizardStyle=modern
-
 [Languages]
 Name: "english"; MessagesFile: "compiler:Default.isl"
-
 [Tasks]
 Name: "desktopicon"; Description: "{cm:CreateDesktopIcon}"; GroupDescription: "{cm:AdditionalIcons}"; Flags: unchecked
-
 ; 定義配對元件，讓使用者選擇是否安裝預設的 Script 與 Model
 [Components]
 Name: "pair1"; Description: "Fire Detection";
 Name: "pair2"; Description: "Photo_quality";
-
+Name: "pair3"; Description: "Test Mode";
 [Files]
 ; 安裝主要執行檔到 {app} 目錄
-Source: "C:\Users\mason\Code\demo_gui\dist\{#MyAppExeName}"; DestDir: "{app}"; Flags: ignoreversion
+Source: "C:\Users\mason\Code\Kneron Academy 2.0\dist\{#MyAppExeName}"; DestDir: "{app}"; Flags: ignoreversion
-
+; 安裝 config.json 檔案 (不需使用者勾選)
+Source: "C:\Users\mason\AppData\Local\Kneron_Academy\utils\config.json"; DestDir: "{localappdata}\Kneron_Academy\utils"; Flags: ignoreversion
 ; --- 配對1 ---
 ; pair 1
-Source: "C:\Users\mason\Downloads\Kneron_Academy\utils\models\fire_detection_520.nef"; DestDir: "{localappdata}\Kneron_Academy\utils\models\fire_detection_520.nef"; Components: pair1; Flags: ignoreversion recursesubdirs
+Source: "C:\Users\mason\AppData\Local\Kneron_Academy\utils\fire detection\yuan\*"; DestDir: "{localappdata}\Kneron_Academy\utils\fire detection\yuan"; Components: pair1; Flags: ignoreversion recursesubdirs createallsubdirs
-Source: "C:\Users\mason\Downloads\Kneron_Academy\utils\scripts\fire_detection_520.py"; DestDir: "{localappdata}\Kneron_Academy\utils\scripts\fire_detection_520.py"; Components: pair1; Flags: ignoreversion recursesubdirs
 ; pair 2
-Source: "C:\Users\mason\Downloads\Kneron_Academy\utils\models\photo_scorer_520.nef"; DestDir: "{localappdata}\Kneron_Academy\utils\models\photo_scorer_520.nef"; Components: pair2; Flags: ignoreversion recursesubdirs
+Source: "C:\Users\mason\AppData\Local\Kneron_Academy\utils\photo quality\ruby\*"; DestDir: "{localappdata}\Kneron_Academy\utils\photo quality\ruby"; Components: pair2; Flags: ignoreversion recursesubdirs createallsubdirs
-Source: "C:\Users\mason\Downloads\Kneron_Academy\utils\scripts\photo_quality_520.py"; DestDir: "{localappdata}\Kneron_Academy\utils\scripts\photo_quality_520.py"; Components: pair2; Flags: ignoreversion recursesubdirs
+; pair 3
-
+Source: "C:\Users\mason\AppData\Local\Kneron_Academy\utils\test mode\test\*"; DestDir: "{localappdata}\Kneron_Academy\utils\test mode\test"; Components: pair3; Flags: ignoreversion recursesubdirs createallsubdirs
 [Dirs]
 ; 如有需要隱藏這些資料夾，設定隱藏屬性
-Name: "{localappdata}\Kneron_Academy\utils\scripts"; Attribs: hidden
+Name: "{localappdata}\Kneron_Academy\utils\fire detection\yuan"; Attribs: hidden
-Name: "{localappdata}\Kneron_Academy\utils\models"; Attribs: hidden
+Name: "{localappdata}\Kneron_Academy\utils\photo quality\ruby"; Attribs: hidden
+Name: "{localappdata}\Kneron_Academy\utils\test mode\test"; Attribs: hidden
 [Icons]
 Name: "{autoprograms}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"
 Name: "{autodesktop}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; Tasks: desktopicon
-
 [Run]
 Filename: "{app}\{#MyAppExeName}"; Description: "{cm:LaunchProgram,{#StringChange(MyAppName, '&', '&&')}}"; Flags: nowait postinstall skipifsilent

src/config.py

@@ -4,12 +4,11 @@ APPDATA_PATH = os.environ.get("LOCALAPPDATA")
 # 取得專案根目錄的絕對路徑並設定 UXUI_ASSETS 為絕對路徑
 PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 UXUI_ASSETS = os.path.join(PROJECT_ROOT, "uxui", "")
-MODEL = os.path.join(APPDATA_PATH,"Kneron_Academy", "utils", "models", "")
+# 新版路徑結構 (不需要獨立的 models 和 scripts 資料夾)
-SCRIPT = os.path.join(APPDATA_PATH, "Kneron_Academy", "utils", "scripts", "")
+UTILS_DIR = os.path.join(APPDATA_PATH, "Kneron_Academy", "utils")
-SCRIPT_CONFIG = os.path.join(APPDATA_PATH, "Kneron_Academy", "utils", "configs.json")
+SCRIPT_CONFIG = os.path.join(UTILS_DIR, "config.json")
 UPLOAD_DIR = os.path.join(APPDATA_PATH, "Kneron_Academy", "uploads")
-FW_DIR = os.path.join(APPDATA_PATH, "Kneron_Academy", "utils", "firmware")
+FW_DIR = os.path.join(APPDATA_PATH, "Kneron_Academy", "firmware")
-
 # Global Constants
 APP_NAME = "Innovedus AI Playground"
 WINDOW_SIZE = (1200, 900)

src/views/mainWindows.py

@@ -8,8 +8,8 @@ from PyQt5.QtCore import Qt, QTimer, QThread, pyqtSignal
 from PyQt5.QtGui import QPixmap, QMovie, QImage
 
 from ..config import (UXUI_ASSETS, WINDOW_SIZE, BACKGROUND_COLOR, SECONDARY_COLOR, 
-                      BUTTON_STYLE, MASK_STYLE, PROJECT_ROOT, SCRIPT_CONFIG, SCRIPT, UPLOAD_DIR,
+                      BUTTON_STYLE, MASK_STYLE, PROJECT_ROOT, SCRIPT_CONFIG, UTILS_DIR , UPLOAD_DIR,
-                      FW_DIR, DongleModelMap, DongleIconMap, MODEL)
+                      FW_DIR, DongleModelMap, DongleIconMap)
 
 from ..services.device_service import check_available_device
 
@@ -56,8 +56,9 @@ def qimage_to_numpy(qimage):
 
 #────────────────────────────────────────────────────────────
 # 動態載入 inference 模組的函式
-def load_inference_module(script_path):
+def load_inference_module(mode, model_name):
-    module_name = os.path.splitext(os.path.basename(script_path))[0]
+    script_path = os.path.join(UTILS_DIR, mode, model_name, "script.py")
+    module_name = f"{mode}_{model_name}"
     spec = importlib.util.spec_from_file_location(module_name, script_path)
     module = importlib.util.module_from_spec(spec)
     spec.loader.exec_module(module)
@@ -70,25 +71,29 @@ class InferenceWorkerThread(QThread):
     # 傳出 inference 結果，型態可依需求調整（例如 dict 或 tuple）
     inference_result_signal = pyqtSignal(object)
 
-    def __init__(self, frame_queue, inference_script_path, min_interval=0.5, mse_threshold=500, once_mode=False):
+    def __init__(self, frame_queue, mode, model_name, min_interval=0.5, mse_threshold=500, once_mode=False):
         """
         frame_queue: 傳入的 frame 佇列(numpy 陣列)
-        inference_script_path: inference 模組的檔案路徑
+        mode: 模式名稱 (如 'face_recognition')
+        model_name: 模型名稱 (如 'face_detection')
         min_interval: 最小 inference 間隔 (秒)
         mse_threshold: 當前後 frame 之均方誤差低於此值則視為相似
         """
         super().__init__()
         self.frame_queue = frame_queue
-        self.inference_script_path = inference_script_path
+        self.mode = mode
+        self.model_name = model_name
         self.min_interval = min_interval
         self.mse_threshold = mse_threshold
         self._running = True
-        self.once_mode = once_mode  # 新增旗標：如果 True，則只做一次推論
+        self.once_mode = once_mode
         self.last_inference_time = 0
         self.last_frame = None
         self.cached_result = None
-        # 動態載入 inference 模組（假設介面函式為 inference(frame, params)）
+        
-        self.inference_module = load_inference_module(self.inference_script_path)
+        # 動態載入 inference 模組
+        script_path = os.path.join(UTILS_DIR, mode, model_name, "script.py")
+        self.inference_module = load_inference_module(mode, model_name)
 
     def run(self):
         while self._running:
@@ -149,12 +154,13 @@ class MainWindow(QWidget):
         self.video_writer = None
         self.recorded_frames = []
         self.destination = None
-        # 目前選用的 tool 配置，初始為 None
         self.current_tool_config = None
         self.inference_worker = None
-        # 建立 frame 佇列，限制最大數量
         self.inference_queue = queue.Queue(maxsize=10)
         
+        # 確保目錄存在並更新配置
+        self.generate_global_config()
+        
         self.init_ui()
         
     def init_ui(self):  # 初始化UI (暫時不需要修改)
@@ -479,28 +485,59 @@ class MainWindow(QWidget):
     def select_tool(self, tool_config):
         print("選擇工具：", tool_config.get("display_name"))
         self.current_tool_config = tool_config
-        new_script_path = os.path.join(SCRIPT, tool_config.get("script"))
         
-        # 取得工具的 input type
+        # 獲取模式和模型名稱
+        mode = tool_config.get("mode", "")
+        model_name = tool_config.get("model_name", "")
+        
+        # 構建模型路徑
+        model_path = os.path.join(UTILS_DIR, mode, model_name)
+        
+        # 讀取特定模型的詳細配置
+        model_config_path = os.path.join(model_path, "config.json")
+        detailed_config = {}
+        
+        if os.path.exists(model_config_path):
+            try:
+                with open(model_config_path, "r", encoding="utf-8") as f:
+                    detailed_config = json.load(f)
+                    # 合併基本配置和詳細配置
+                    tool_config = {**tool_config, **detailed_config}
+            except Exception as e:
+                print(f"Error reading model config: {e}")
+        
+        # 獲取工具的輸入類型
         input_info = tool_config.get("input_info", {})
         tool_type = input_info.get("type", "video")
         print("type:", tool_type)
         once_mode = True if tool_type == "image" else False
 
-        # 組合 input_params（從 tool_config 中預設值）
+        # 組合input_params
         input_params = tool_config.get("input_parameters", {}).copy()
         
+        # 處理設備相關設定
         if hasattr(self, "selected_device") and self.selected_device:
             input_params["usb_port_id"] = self.selected_device.get("usb_port_id", 0)
-            # 直接使用設備的 model（在 parse_and_store_devices 已填入）
             dongle = self.selected_device.get("dongle", "unknown")
             print("選取的 dongle:", dongle)
-            # 利用 model 當作子資料夾名稱組合 firmware 路徑
+            
+            # 檢查模型是否支援該設備
+            compatible_devices = tool_config.get("compatible_devices", [])
+            if compatible_devices and dongle not in compatible_devices:
+                self.show_custom_message(
+                    QMessageBox.Warning, 
+                    "設備不兼容", 
+                    f"所選模型不支援 {dongle} 設備。\n支援的設備: {', '.join(compatible_devices)}"
+                )
+                return
+                
+            # 處理韌體路徑
             scpu_path = os.path.join(FW_DIR, dongle, "fw_scpu.bin")
             ncpu_path = os.path.join(FW_DIR, dongle, "fw_ncpu.bin")
             input_params["scpu_path"] = scpu_path
             input_params["ncpu_path"] = ncpu_path
         else:
+            # 預設設備處理邏輯不變
             if self.connected_devices and len(self.connected_devices) > 0:
                 input_params["usb_port_id"] = self.connected_devices[0].get("usb_port_id", 0)
                 print("Warning: 沒有特別選取 dongle, 預設使用第一個設備")
@@ -508,11 +545,11 @@ class MainWindow(QWidget):
                 input_params["usb_port_id"] = 0
                 print("Warning: 沒有連接設備, 使用預設 usb_port_id 0")
 
-        # 若工具模式需要檔案輸入，則處理 file_path
+        # 處理檔案輸入
         if tool_type in ["image", "voice"]:
+            # 處理邏輯不變
             if hasattr(self, "destination") and self.destination:
                 input_params["file_path"] = self.destination
-                # 讀取上傳的圖片並推入 inference_queue
                 uploaded_img = cv2.imread(self.destination)
                 if uploaded_img is not None:
                     if not self.inference_queue.full():
@@ -526,12 +563,11 @@ class MainWindow(QWidget):
                 input_params["file_path"] = ""
                 print("Warning: 需要檔案輸入，但尚未上傳檔案。")
         
-        # 從 config 讀取 model_info，組合 model 路徑
+        # 添加模型檔案路徑
-        if "model_info" in tool_config:
+        if "model_file" in tool_config:
-            model_name = tool_config["model_info"].get("name", "")
+            model_file = tool_config["model_file"]
-            # 假設模型檔案存放在 "src\\utils\\models" 資料夾下，根據需要調整路徑
+            model_file_path = os.path.join(model_path, model_file)
-            model_path = os.path.join(MODEL, model_name)
+            input_params["model"] = model_file_path
-            input_params["model"] = model_path
         
         print("input_params:", input_params)
 
@@ -540,10 +576,11 @@ class MainWindow(QWidget):
             self.inference_worker.stop()
             self.inference_worker = None
 
-        # 建立新的 inference worker
+        # 建立新的 inference worker (使用修改後的參數)
         self.inference_worker = InferenceWorkerThread(
             self.inference_queue,
-            new_script_path,
+            mode,
+            model_name,
             min_interval=0.5,
             mse_threshold=500,
             once_mode=once_mode
@@ -551,7 +588,7 @@ class MainWindow(QWidget):
         self.inference_worker.input_params = input_params
         self.inference_worker.inference_result_signal.connect(self.handle_inference_result)
         self.inference_worker.start()
-        print(f"Inference worker 已切換到模組：{new_script_path}")
+        print(f"Inference worker 已切換到模組：{mode}/{model_name}")
 
         if tool_type == "video":
             self.start_camera()
@@ -566,20 +603,21 @@ class MainWindow(QWidget):
             if os.path.exists(SCRIPT_CONFIG):
                 with open(SCRIPT_CONFIG, "r", encoding="utf-8") as f:
                     config = json.load(f)
-                tools = config.get("tools", [])
+                plugins = config.get("plugins", [])
-                # print("tools: ", tools)
             else:
-                print("找不到 toolbox config 檔案，使用空的工具列表")
+                # 若無配置檔，則嘗試自動生成
-                tools = []
+                plugins = self.generate_global_config().get("plugins", [])
+                if not plugins:
+                    print("無法生成配置，使用空的工具列表")
             
-            # 建立工具箱介面
+            # 創建工具箱UI
             toolbox_frame = QFrame(self)
             toolbox_frame.setStyleSheet(f"border: none; background: {SECONDARY_COLOR}; border-radius: 15px;")
             toolbox_frame.setFixedHeight(450)
             toolbox_frame.setFixedWidth(240)
             toolbox_layout = QVBoxLayout(toolbox_frame)
             
-            # 建立標題列
+            # 標題列
             title_layout = QHBoxLayout()
             title_container = QWidget()
             container_layout = QHBoxLayout(title_container)
@@ -596,12 +634,33 @@ class MainWindow(QWidget):
             title_layout.addWidget(title_container)
             toolbox_layout.addLayout(title_layout)
             
-            # 根據 JSON 配置建立工具按鈕
+            # 建立工具按鈕 (分類顯示)
-            for tool in tools:
+            for plugin in plugins:
-                name = tool.get("display_name", "Unnamed Tool")
+                mode = plugin.get("mode", "")
-                button = QPushButton(name)
+                display_name = plugin.get("display_name", "")
-                # 使用 lambda 捕捉 tool 設定，避免 late binding 問題
+                
-                button.clicked.connect(lambda checked, t=tool: self.select_tool(t))
+                # 添加分類標題
+                category_label = QLabel(display_name)
+                category_label.setStyleSheet("color: white; font-size: 16px; font-weight: bold; margin-top: 10px;")
+                toolbox_layout.addWidget(category_label)
+                
+                # 添加該分類下的所有模型按鈕
+                for model in plugin.get("models", []):
+                    model_name = model.get("name", "")
+                    display_name = model.get("display_name", "")
+                    
+                    # 建立工具配置
+                    tool_config = {
+                        "mode": mode,
+                        "model_name": model_name,
+                        "display_name": display_name,
+                        "description": model.get("description", ""),
+                        "compatible_devices": model.get("compatible_devices", [])
+                    }
+                    
+                    # 建立按鈕
+                    button = QPushButton(display_name)
+                    button.clicked.connect(lambda checked, t=tool_config: self.select_tool(t))
                     button.setStyleSheet(BUTTON_STYLE)
                     button.setFixedHeight(40)
                     toolbox_layout.addWidget(button)
@@ -1141,3 +1200,84 @@ class MainWindow(QWidget):
             self.overlay.hide()
         except Exception as e:
             print(f"Error in hide_device_popup: {e}")
+
+    def generate_global_config(self):
+        """掃描目錄結構並生成全局配置檔案"""
+        try:
+            config = {"plugins": []}
+            
+            # 確認 utils 目錄存在
+            if not os.path.exists(UTILS_DIR):
+                os.makedirs(UTILS_DIR, exist_ok=True)
+                print(f"已建立 UTILS_DIR: {UTILS_DIR}")
+            
+            # 列出 utils 目錄下的所有項目以進行偵錯
+            print(f"UTILS_DIR 內容: {os.listdir(UTILS_DIR) if os.path.exists(UTILS_DIR) else '目錄不存在'}")
+            
+            # 掃描模式目錄（第一層子目錄）
+            mode_dirs = [d for d in os.listdir(UTILS_DIR) 
+                        if os.path.isdir(os.path.join(UTILS_DIR, d)) and not d.startswith('_')]
+            
+            print(f"找到的模式目錄: {mode_dirs}")
+            
+            for mode_name in mode_dirs:
+                mode_path = os.path.join(UTILS_DIR, mode_name)
+                
+                mode_info = {
+                    "mode": mode_name,
+                    "display_name": mode_name.replace("_", " ").title(),
+                    "models": []
+                }
+                
+                # 列出該模式目錄下的所有項目以進行偵錯
+                print(f"模式 {mode_name} 的內容: {os.listdir(mode_path)}")
+                
+                # 掃描模型目錄（第二層子目錄）
+                model_dirs = [d for d in os.listdir(mode_path) 
+                            if os.path.isdir(os.path.join(mode_path, d)) and not d.startswith('_')]
+                
+                print(f"在模式 {mode_name} 中找到的模型: {model_dirs}")
+                
+                for model_name in model_dirs:
+                    model_path = os.path.join(mode_path, model_name)
+                    
+                    # 檢查模型配置檔案
+                    model_config_path = os.path.join(model_path, "config.json")
+                    if os.path.exists(model_config_path):
+                        try:
+                            with open(model_config_path, "r", encoding="utf-8") as f:
+                                model_config = json.load(f)
+                            
+                            print(f"已成功讀取模型配置: {model_config_path}")
+                            
+                            model_summary = {
+                                "name": model_name,
+                                "display_name": model_config.get("display_name", model_name.replace("_", " ").title()),
+                                "description": model_config.get("description", ""),
+                                "compatible_devices": model_config.get("compatible_devices", [])
+                            }
+                            
+                            mode_info["models"].append(model_summary)
+                        except Exception as e:
+                            print(f"讀取模型配置時發生錯誤 {model_config_path}: {e}")
+                    else:
+                        print(f"未找到模型配置檔: {model_config_path}")
+                        # 可選：自動創建模板配置檔
+                        self.create_model_config_template(model_path)
+                
+                # 只添加含有模型的模式
+                if mode_info["models"]:
+                    config["plugins"].append(mode_info)
+            
+            # 寫入配置檔
+            os.makedirs(os.path.dirname(SCRIPT_CONFIG), exist_ok=True)
+            with open(SCRIPT_CONFIG, "w", encoding="utf-8") as f:
+                json.dump(config, f, indent=2, ensure_ascii=False)
+            
+            print(f"全局配置已生成: {SCRIPT_CONFIG}")
+            return config
+        except Exception as e:
+            print(f"生成全局配置時發生錯誤: {e}")
+            import traceback
+            traceback.print_exc()
+            return {"plugins": []}