refactor: 新增 ui.js 和 main.js 模組，啟用 ES6 Modules

新增檔案：
- js/ui.js - UI 操作、模組切換、預覽更新、表單資料收集
- js/main.js - 主程式初始化、事件監聽器設置、快捷鍵

更新檔案：
- index.html - 引用 ES6 模組 (type="module")

功能：
✅ 模組切換功能
✅ 標籤頁切換
✅ 表單欄位監聽
✅ JSON 預覽更新
✅ 快捷鍵支援 (Ctrl+S, Ctrl+N)
✅ 用戶信息載入
✅ 登出功能

注意：
- 大部分 JavaScript 代碼仍在 HTML 中（約 2400 行）
- 已建立核心模組架構，便於後續逐步遷移
- 使用 ES6 Modules，需要通過 HTTP Server 運行

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

llm_config.py

@@ -7,6 +7,10 @@ import os
 import requests
 from dotenv import load_dotenv
 from typing import Dict, List, Tuple
+import urllib3
+
+# Disable SSL warnings for Ollama endpoint
+urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
 # Load environment variables
 load_dotenv()
@@ -34,6 +38,20 @@ class LLMConfig:
                 'api_key': os.getenv('OPENAI_API_KEY', ''),
                 'endpoint': os.getenv('OPENAI_API_URL', 'https://api.openai.com/v1'),
                 'enabled': bool(os.getenv('OPENAI_API_KEY'))
+            },
+            'ollama': {
+                'name': 'Ollama',
+                'api_key': '',  # Ollama 不需要 API Key
+                'endpoint': os.getenv('OLLAMA_API_URL', 'https://ollama_pjapi.theaken.com'),
+                'model': os.getenv('OLLAMA_MODEL', 'qwen2.5:3b'),
+                'enabled': True  # Ollama 預設啟用
+            },
+            'gptoss': {
+                'name': 'GPT-OSS',
+                'api_key': '',  # GPT-OSS 不需要 API Key (使用 Ollama 介面)
+                'endpoint': os.getenv('GPTOSS_API_URL', 'https://ollama_pjapi.theaken.com'),
+                'model': os.getenv('GPTOSS_MODEL', 'gpt-oss:120b'),
+                'enabled': True  # GPT-OSS 預設啟用
             }
         }
 
@@ -153,6 +171,35 @@ class LLMConfig:
         except Exception as e:
             return False, f"錯誤: {str(e)}"
 
+    def test_ollama_connection(self) -> Tuple[bool, str]:
+        """Test Ollama API connection"""
+        try:
+            endpoint = self.apis['ollama']['endpoint']
+
+            # Test endpoint - list models
+            url = f"{endpoint}/v1/models"
+
+            response = requests.get(url, timeout=10, verify=False)
+
+            if response.status_code == 200:
+                data = response.json()
+                models = data.get('data', [])
+                if models:
+                    model_count = len(models)
+                    model_names = [m.get('id', '') for m in models[:3]]
+                    return True, f"連線成功！找到 {model_count} 個可用模型 (例如: {', '.join(model_names)})"
+                else:
+                    return True, "連線成功！"
+            else:
+                return False, f"連線失敗 (HTTP {response.status_code})"
+
+        except requests.exceptions.Timeout:
+            return False, "連線逾時"
+        except requests.exceptions.ConnectionError:
+            return False, "無法連接到伺服器"
+        except Exception as e:
+            return False, f"錯誤: {str(e)}"
+
     def test_all_connections(self) -> Dict[str, Tuple[bool, str]]:
         """Test all configured API connections"""
         results = {}
@@ -166,6 +213,9 @@ class LLMConfig:
         if self.apis['openai']['enabled']:
             results['openai'] = self.test_openai_connection()
 
+        if self.apis['ollama']['enabled']:
+            results['ollama'] = self.test_ollama_connection()
+
         return results
 
     def generate_text_gemini(self, prompt: str, max_tokens: int = 2000) -> Tuple[bool, str]:
@@ -175,7 +225,9 @@ class LLMConfig:
             if not api_key:
                 return False, "API Key 未設定"
 
-            url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key={api_key}"
+            # 從環境變數讀取模型名稱，默認使用 gemini-1.5-flash
+            model_name = os.getenv('GEMINI_MODEL', 'gemini-1.5-flash')
+            url = f"https://generativelanguage.googleapis.com/v1beta/models/{model_name}:generateContent?key={api_key}"
 
             data = {
                 "contents": [
@@ -275,6 +327,86 @@ class LLMConfig:
         except Exception as e:
             return False, f"錯誤: {str(e)}"
 
+    def generate_text_ollama(self, prompt: str, max_tokens: int = 2000, model: str = None) -> Tuple[bool, str]:
+        """Generate text using Ollama API
+
+        Args:
+            prompt: The prompt text
+            max_tokens: Maximum tokens to generate (not used by Ollama but kept for compatibility)
+            model: The model to use. If None, uses the default from config.
+        """
+        try:
+            endpoint = self.apis['ollama']['endpoint']
+            # 使用傳入的 model 參數，如果沒有則使用設定檔中的預設值
+            if model is None:
+                model = self.apis['ollama']['model']
+
+            url = f"{endpoint}/v1/chat/completions"
+            headers = {
+                'Content-Type': 'application/json'
+            }
+
+            data = {
+                "model": model,
+                "messages": [
+                    {"role": "system", "content": "You are a helpful assistant."},
+                    {"role": "user", "content": prompt}
+                ],
+                "temperature": 0.7
+            }
+
+            response = requests.post(url, json=data, headers=headers, timeout=60, verify=False)
+
+            if response.status_code == 200:
+                result = response.json()
+                text = result['choices'][0]['message']['content']
+                return True, text
+            else:
+                return False, f"生成失敗 (HTTP {response.status_code}): {response.text}"
+
+        except Exception as e:
+            return False, f"錯誤: {str(e)}"
+
+    def generate_text_gptoss(self, prompt: str, max_tokens: int = 2000, model: str = None) -> Tuple[bool, str]:
+        """Generate text using GPT-OSS API (120B model via Ollama interface)
+
+        Args:
+            prompt: The prompt text
+            max_tokens: Maximum tokens to generate (not used by Ollama but kept for compatibility)
+            model: The model to use. If None, uses the default from config.
+        """
+        try:
+            endpoint = self.apis['gptoss']['endpoint']
+            # 使用傳入的 model 參數，如果沒有則使用設定檔中的預設值
+            if model is None:
+                model = self.apis['gptoss']['model']
+
+            url = f"{endpoint}/v1/chat/completions"
+            headers = {
+                'Content-Type': 'application/json'
+            }
+
+            data = {
+                "model": model,
+                "messages": [
+                    {"role": "system", "content": "You are a helpful assistant."},
+                    {"role": "user", "content": prompt}
+                ],
+                "temperature": 0.7
+            }
+
+            response = requests.post(url, json=data, headers=headers, timeout=60, verify=False)
+
+            if response.status_code == 200:
+                result = response.json()
+                text = result['choices'][0]['message']['content']
+                return True, text
+            else:
+                return False, f"生成失敗 (HTTP {response.status_code}): {response.text}"
+
+        except Exception as e:
+            return False, f"錯誤: {str(e)}"
+
 
 def main():
     """Test script"""