Initial commit: Daily News App

企業內部新聞彙整與分析系統
- 自動新聞抓取 (Digitimes, 經濟日報, 工商時報)
- AI 智慧摘要 (OpenAI/Claude/Ollama)
- 群組管理與訂閱通知
- 已清理 Python 快取檔案

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

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

app/services/llm_service.py

@@ -0,0 +1,176 @@
+"""
+LLM 服務模組
+支援 Google Gemini、OpenAI、Ollama
+"""
+import time
+from typing import Optional
+import httpx
+
+from app.core.config import settings
+
+
+def get_llm_client():
+    """取得 LLM 客戶端"""
+    provider = settings.llm_provider
+    
+    if provider == "gemini":
+        import google.generativeai as genai
+        genai.configure(api_key=settings.gemini_api_key)
+        return genai
+    elif provider == "openai":
+        from openai import OpenAI
+        return OpenAI(api_key=settings.openai_api_key)
+    elif provider == "ollama":
+        return None  # 使用 httpx 直接呼叫
+    
+    raise ValueError(f"不支援的 LLM 提供者: {provider}")
+
+
+def generate_summary(group, articles: list) -> str:
+    """
+    產生 AI 摘要
+    
+    Args:
+        group: 群組物件（包含 ai_background, ai_prompt）
+        articles: 新聞文章列表
+    
+    Returns:
+        綜合摘要文字
+    """
+    if not articles:
+        return "無相關新聞可供摘要。"
+    
+    # 組合文章內容
+    articles_text = ""
+    for i, article in enumerate(articles, 1):
+        articles_text += f"""
+---
+新聞 {i}：{article.title}
+來源：{article.source.name if article.source else '未知'}
+內容：{article.content[:1000] if article.content else article.summary or '無內容'}
+---
+"""
+    
+    # 建立 Prompt
+    system_prompt = f"""你是一位專業的產業分析師，負責彙整每日新聞並產出精闘的綜合分析報告。
+
+背景資訊：
+{group.ai_background or '無特定背景資訊'}
+
+摘要方向：
+{group.ai_prompt or '請綜合分析以下新聞的重點、趨勢與潛在影響。'}
+"""
+    
+    user_prompt = f"""請根據以下 {len(articles)} 則新聞，產出一份繁體中文的綜合分析報告：
+
+{articles_text}
+
+請注意：
+1. 使用繁體中文
+2. 整合相關主題，避免逐條列舉
+3. 突出重要趨勢與影響
+4. 控制在 500 字以內
+"""
+    
+    provider = settings.llm_provider
+    
+    try:
+        if provider == "gemini":
+            import google.generativeai as genai
+            genai.configure(api_key=settings.gemini_api_key)
+            model = genai.GenerativeModel(settings.gemini_model or "gemini-1.5-pro")
+            response = model.generate_content(
+                f"{system_prompt}\n\n{user_prompt}",
+                generation_config={
+                    "temperature": 0.7,
+                    "max_output_tokens": 2048,
+                    "top_p": 0.95,
+                    "top_k": 40
+                }
+            )
+            return response.text
+        
+        elif provider == "openai":
+            from openai import OpenAI
+            client = OpenAI(api_key=settings.openai_api_key)
+            response = client.chat.completions.create(
+                model=settings.openai_model or "gpt-4o",
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": user_prompt}
+                ],
+                max_tokens=2048,
+                temperature=0.7
+            )
+            return response.choices[0].message.content
+        
+        elif provider == "ollama":
+            response = httpx.post(
+                f"{settings.ollama_endpoint}/api/generate",
+                json={
+                    "model": settings.ollama_model or "llama3",
+                    "prompt": f"{system_prompt}\n\n{user_prompt}",
+                    "stream": False,
+                    "options": {
+                        "temperature": 0.7,
+                        "num_predict": 2048,
+                        "top_p": 0.9,
+                        "top_k": 40
+                    }
+                },
+                timeout=120
+            )
+            return response.json().get("response", "")
+        
+    except Exception as e:
+        return f"摘要產生失敗：{str(e)}"
+
+
+def test_llm_connection(provider: str, model: str) -> dict:
+    """
+    測試 LLM 連線
+    
+    Returns:
+        {"success": bool, "response_time_ms": int, "message": str}
+    """
+    start_time = time.time()
+    
+    try:
+        if provider == "gemini":
+            import google.generativeai as genai
+            genai.configure(api_key=settings.gemini_api_key)
+            gen_model = genai.GenerativeModel(model)
+            response = gen_model.generate_content(
+                "Hello",
+                generation_config={"max_output_tokens": 10}
+            )
+            elapsed = int((time.time() - start_time) * 1000)
+            return {"success": True, "response_time_ms": elapsed}
+        
+        elif provider == "openai":
+            from openai import OpenAI
+            client = OpenAI(api_key=settings.openai_api_key)
+            response = client.chat.completions.create(
+                model=model,
+                messages=[{"role": "user", "content": "Hello"}],
+                max_tokens=10
+            )
+            elapsed = int((time.time() - start_time) * 1000)
+            return {"success": True, "response_time_ms": elapsed}
+        
+        elif provider == "ollama":
+            response = httpx.post(
+                f"{settings.ollama_endpoint}/api/generate",
+                json={"model": model, "prompt": "Hello", "stream": False},
+                timeout=30
+            )
+            elapsed = int((time.time() - start_time) * 1000)
+            if response.status_code == 200:
+                return {"success": True, "response_time_ms": elapsed}
+            return {"success": False, "message": f"HTTP {response.status_code}"}
+        
+        return {"success": False, "message": f"不支援的提供者: {provider}"}
+        
+    except Exception as e:
+        elapsed = int((time.time() - start_time) * 1000)
+        return {"success": False, "response_time_ms": elapsed, "message": str(e)}