command_handler.py

# command_handler.py
import pandas as pd
from linebot.v3.messaging import TextMessage, ImageMessage

# ... (匯入服務函式部分不變) ...
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
from weather_service import fetch_forecast_by_location
from config import CURRENT_YEAR, HF_SPACE_URL

# ... (get_help_message, get_info_message 函式不變) ...
def get_help_message():
    #...
    return TextMessage(text=text)

def get_info_message():
    #...
    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]
        
        # [修改] 從 row 中讀取 'url' 並加入訊息中
        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"
                f"地點: {row['place']}\n"
                f"報告連結: {row.get('url', '無')}"
            )

        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)]

# ... (process_message 函式不變) ...
def process_message(user_message_raw: str, request_base_url: str) -> list:
    # ...
    return [TextMessage(text=generate_ai_text(user_message))]