Update ai_service.py

ai_service.py

@@ -1,4 +1,4 @@
-# ai_service.py (Implements robust API key validation and rotation)
+# ai_service.py (Instructs AI to execute tool calls without asking for confirmation)
 import json
 import os
 import random
@@ -10,46 +10,29 @@ from gradio_client import Client
 # 從設定檔匯入金鑰和 URL
 from config import MCP_SERVER_URL
 
-# --- 1. [核心修改] API 金鑰健康檢查與輪替機制 ---
-
-# 從環境變數讀取您設定的兩組金鑰
+# --- 1. API 金鑰健康檢查與輪替機制 ---
 key1 = os.getenv("GEMINI_API_KEY")
 key2 = os.getenv("GEMINI_API_KEY2")
-
 all_keys = []
-if key1 and "YOUR_GEMINI_API_KEY" not in key1:
-    all_keys.append(key1)
-if key2 and "YOUR_GEMINI_API_KEY" not in key2:
-    all_keys.append(key2)
+if key1 and "YOUR_GEMINI_API_KEY" not in key1: all_keys.append(key1)
+if key2 and "YOUR_GEMINI_API_KEY" not in key2: all_keys.append(key2)
 
-# 建立一個存放 "健康" (有效) 金鑰的列表
 healthy_keys = []
 if all_keys:
     print(f"--- Found {len(all_keys)} Gemini API Key(s). Starting validation... ---")
     for key in all_keys:
         try:
-            # 嘗試用每個 key 來設定並初始化一個模型，以驗證其有效性
             genai.configure(api_key=key)
-            # 嘗試發送一個非常簡單的測試請求
             test_model = genai.GenerativeModel('gemini-1.5-flash')
             test_model.generate_content("test", request_options={'timeout': 10})
-            
-            # 如果成功，將此 key 加入健康列表
             healthy_keys.append(key)
             print(f"--- Key ending in ...{key[-4:]} is VALID and added to the pool. ---")
-        except google_exceptions.PermissionDenied as e:
-            print(f"--- Key ending in ...{key[-4:]} is INVALID (Permission Denied). Skipping. ---")
-            print(f"    Error details: {e}")
         except Exception as e:
-            # 捕捉其他可能的錯誤，例如超時、額度用盡等
-            print(f"--- Key ending in ...{key[-4:]} failed validation. Skipping. ---")
-            print(f"    Error details: {e}")
-
+            print(f"--- Key ending in ...{key[-4:]} failed validation. Skipping. Error: {e} ---")
 if not healthy_keys:
     print("--- CRITICAL: No valid Gemini API Keys found. AI Service will be disabled. ---")
 
-# --- 2. 工具函式 (Tool Functions) --- (此區塊維持不變)
-
+# --- 2. 工具函式 (Tool Functions) ---
 def call_mcp_earthquake_search(start_date: str, end_date: str, min_magnitude: float = 4.0, max_magnitude: float = 9.0) -> str:
     try:
         client = Client(src=MCP_SERVER_URL)
@@ -67,36 +50,35 @@ def call_mcp_pws_search() -> str:
         return result[0] if isinstance(result, tuple) and len(result) > 0 else str(result)
     except Exception as e: return f"工具執行失敗，錯誤訊息: {e}"
 
-# --- 3. 向 Gemini 定義工具 (Tool Declarations) --- (此區塊維持不變)
-# ... (此處省略與上一版相同的工具定義程式碼)
+# --- 3. 向 Gemini 定義工具 (Tool Declarations) ---
 earthquake_search_tool_declaration = { "name": "call_earthquake_search_tool", "description": "從台灣中央氣象署的資料庫中搜尋地震事件。", "parameters": { "type": "OBJECT", "properties": { "start_date": { "type": "STRING", "description": "搜尋的開始日期 (格式 'YYYY-MM-DD')。模型應根據使用者問題中的相對時間（例如：昨天、上個月、去年）或絕對時間（例如：2024年）來主動推斷此日期。" }, "end_date": { "type": "STRING", "description": "搜尋的結束日期 (格式 'YYYY-MM-DD')。模型應根據使用者問題中的相對時間或絕對時間來主動推斷此日期。" }, }, "required": ["start_date", "end_date"] } }
 pws_search_tool_declaration = { "name": "call_mcp_pws_search", "description": "查詢最新的 PWS (Public Weather Service) 公共天氣服務發布情形。", "parameters": { "type": "OBJECT", "properties": {} } }
 available_tools = { "call_earthquake_search_tool": call_mcp_earthquake_search, "call_mcp_pws_search": call_mcp_pws_search }
 
 # --- 4. 主要的 AI 文字生成函式 ---
-
 def generate_ai_text(user_prompt: str) -> str:
-    # [核心修改] 每次呼叫時，都從健康的金鑰池中隨機選取
     if not healthy_keys:
         return "🤖 AI (Gemini) 服務錯誤：沒有任何有效的 API 金鑰可供使用。"
     
     try:
-        # 從健康池中隨機選擇一個 key
         selected_key = random.choice(healthy_keys)
         print(f"--- Handling request with key ending in: ...{selected_key[-4:]} ---")
         
-        # 使用選定的 key 建立模型實例
         genai.configure(api_key=selected_key)
+        
+        # [*** 核心修正 ***]
+        # 在系統指令中，明確要求 AI 在推斷出參數後「不要提問，直接執行」
+        system_instruction = (
+            "You are a helpful AI assistant. You must answer in Traditional Chinese."
+            "When a user's query can be answered by a tool, you MUST infer the parameters from the query and call the tool immediately without asking for confirmation. Do not ask the user to confirm the parameters you have inferred."
+            "When the user asks for the 'largest' or 'strongest' earthquake, you MUST assume they mean by magnitude. You should then analyze the JSON data returned by the tool, "
+            "find the single entry with the highest 'magnitude' value, and present that specific earthquake's details as the answer."
+        )
+        
         model = genai.GenerativeModel(
             model_name="gemini-1.5-flash",
             tools=[earthquake_search_tool_declaration, pws_search_tool_declaration],
-            system_instruction=(
-                "You are a helpful AI assistant. You must answer in Traditional Chinese."
-                "When the user asks for the 'largest' or 'strongest' earthquake, "
-                "you MUST assume they mean by magnitude. You should then analyze the JSON data returned by the tool, "
-                "find the single entry with the highest 'magnitude' value, and present that specific earthquake's details as the answer."
-                "Do not simply show all the data; find the maximum and answer the question directly."
-            )
+            system_instruction=system_instruction
         )
         
         chat = model.start_chat()