Update command_handler.py

command_handler.py

@@ -3,7 +3,7 @@ import pandas as pd
 from linebot.v3.messaging import TextMessage, ImageMessage
 
 # 匯入服務函式
-from cwa_service import fetch_cwa_alarm_list, fetch_significant_earthquakes # [新增]
+from cwa_service import fetch_cwa_alarm_list, fetch_significant_earthquakes
 from usgs_service import fetch_global_last24h_text, fetch_taiwan_df_this_year
 from plotting_service import create_and_save_map
 from ai_service import generate_ai_text
@@ -19,7 +19,7 @@ def get_help_message() -> TextMessage:
         "• /taiwan - 顯示今年台灣顯著地震列表\n"
         "• /map - 繪製台灣顯著地震地圖\n"
         "• /alert - 獲取 CWA 最新地震預警\n"
-        "• /significant - CWA 最新顯著有感地震\n\n" # [新增]
+        "• /significant - CWA 最新顯著有感地震\n\n"
         "【AI 與工具】\n"
         "• /ai <問題> - 與 AI 助理對話\n"
         "• /weather <地點> - 查詢天氣預報\n\n"
@@ -29,10 +29,60 @@ def get_help_message() -> TextMessage:
     )
     return TextMessage(text=text)
 
-# ... (get_info_message, get_taiwan_earthquake_list, get_taiwan_earthquake_map 函式不變) ...
+def get_info_message() -> TextMessage:
+    """回傳機器人資訊。"""
+    text = (
+        "🤖 關於我\n\n"
+        "我是一個多功能助理機器人，提供地震查詢、天氣資訊與 AI 對話功能。\n\n"
+        "• 版本: 2.0\n"
+        "• 資料來源: CWA, USGS, Hugging Face\n"
+        "• 開發者: dayichen"
+    )
+    return TextMessage(text=text)
+
+def get_taiwan_earthquake_list() -> TextMessage:
+    """回傳近期的台灣地震文字列表。"""
+    result = fetch_taiwan_df_this_year()
+    if isinstance(result, pd.DataFrame):
+        count = len(result)
+        lines = [f"🇹🇼 今年 ({CURRENT_YEAR} 年) 台灣區域顯著地震 (M≥5.0)，共 {count} 筆:", "-" * 20]
+        for _, row in result.head(15).iterrows():
+            t = row["time_utc"].strftime("%Y-%m-%d %H:%M")
+            lines.append(f"震級: {row['magnitude']:.1f} | 日期時間: {t} (UTC)\n地點: {row['place']}")
+        if count > 15:
+            lines.append(f"... (還有 {count - 15} 筆，請用 /map 查看全部)")
+        reply_text = "\n\n".join(lines)
+    else:
+        reply_text = result
+    return TextMessage(text=reply_text)
+
+def get_taiwan_earthquake_map(base_url: str) -> list:
+    """產生並回傳台灣地震地圖的訊息。"""
+    result = fetch_taiwan_df_this_year()
+    if isinstance(result, pd.DataFrame):
+        filename = create_and_save_map(result)
+        image_url = f"{(HF_SPACE_URL or base_url)}/static/{filename}"
+        return [
+            TextMessage(text="🗺️ 已為您繪製今年台灣區域 M≥5.0 地震分佈圖（UTC）。"),
+            ImageMessage(original_content_url=image_url, preview_image_url=image_url),
+        ]
+    else:
+        return [TextMessage(text=result)]
 
 def process_message(user_message_raw: str, request_base_url: str) -> list:
-    # ... (舊指令相容性轉換不變) ...
+    """處理使用者的文字訊息並回傳一個包含回覆訊息的列表。"""
+    # [修正] 加上這一行來定義 user_message 變數
+    user_message = (user_message_raw or "").strip()
+    
+    # 將舊指令對應到新指令，提供向下相容
+    if user_message.lower() in ["地震", "quake"]:
+        user_message = "/global"
+    elif user_message.lower() in ["台灣地震", "臺灣地震"]:
+        user_message = "/taiwan"
+    elif user_message.lower() in ["台灣地震畫圖", "臺灣地震畫圖"]:
+        user_message = "/map"
+    elif user_message.lower() == "地震預警":
+        user_message = "/alert"
 
     if user_message.startswith('/'):
         parts = user_message.split(' ', 1)
@@ -43,18 +93,24 @@ def process_message(user_message_raw: str, request_base_url: str) -> list:
             return [get_help_message()]
         elif command == '/info':
             return [get_info_message()]
-        # ... (其他 command 判斷不變) ...
+        elif command == '/global':
+            return [TextMessage(text=fetch_global_last24h_text())]
+        elif command == '/taiwan':
+            return [get_taiwan_earthquake_list()]
         elif command == '/map':
             return get_taiwan_earthquake_map(request_base_url)
         elif command == '/alert':
             return [TextMessage(text=fetch_cwa_alarm_list(limit=5))]
-        elif command == '/significant': # [新增]
+        elif command == '/significant':
             return [TextMessage(text=fetch_significant_earthquakes(limit=5))]
         elif command == '/weather':
             if not arg:
                 return [TextMessage(text="請輸入地點，例如：/weather 台北")]
             return [TextMessage(text=fetch_forecast_by_location(arg))]
-        # ... (其餘部分不變) ...
+        elif command == '/ai':
+            if not arg:
+                return [TextMessage(text="請輸入問題，例如：/ai 台灣最高的山是哪座？")]
+            return [TextMessage(text=generate_ai_text(arg))]
 
     # 若非指令，則預設交給 AI 處理 (作為備援)
     return [TextMessage(text=generate_ai_text(user_message))]