diff --git a/bot_listener.py b/bot_listener.py index b2d65c7d..ba0b2362 100644 --- a/bot_listener.py +++ b/bot_listener.py @@ -37,7 +37,7 @@ def start_bot(): config = load_config() token = os.getenv("TELEGRAM_BOT_TOKEN") if not token: - logger.error("鏈壘鍒?TELEGRAM_BOT_TOKEN 鐜鍙橀噺") + logger.error("未找到 TELEGRAM_BOT_TOKEN 环境变量") return bot = telebot.TeleBot(token) @@ -77,15 +77,15 @@ def start_bot(): @bot.message_handler(commands=["start", "help"]) def send_welcome(message): welcome_text = ( - "馃尅锔?PolyWeather 澶╂皵鏌ヨ鏈哄櫒浜?/b>\n\n" - "鍙敤鎸囦护:\n" - f"/city [鍩庡競鍚峕 - 鏌ヨ鍩庡競澶╂皵棰勬祴涓庡疄娴?(娑堣€?{CITY_QUERY_COST} 绉垎)\n" - f"/deb [鍩庡競鍚峕 - 鏌ョ湅 DEB 铻嶅悎棰勬祴鍑嗙‘鐜?(娑堣€?{DEB_QUERY_COST} 绉垎)\n" - "/top - 鏌ョ湅绉垎鎺掕姒淺n" - "/id - 鑾峰彇褰撳墠鑱婂ぉ鐨?Chat ID\n\n" - "绀轰緥: /city 浼︽暒\n" - f"馃挕 鎻愮ず: 姣忔棩绛惧埌(鏈夋晥鍙戣█婊?{MESSAGE_MIN_LENGTH} 瀛?鑾峰緱 {MESSAGE_POINTS} 绉垎锛? - f"姣忔棩涓婇檺 {MESSAGE_DAILY_CAP} 鍒嗐€?/i>" + "🚀 PolyWeather 天气查询机器人\n\n" + "可用指令:\n" + f"/city [城市名] - 查询城市天气预测与实测 (消耗 {CITY_QUERY_COST} 积分)\n" + f"/deb [城市名] - 查看 DEB 融合预测准确率 (消耗 {DEB_QUERY_COST} 积分)\n" + "/top - 查看积分排行榜\n" + "/id - 获取当前聊天的 Chat ID\n\n" + "示例: /city 伦敦\n" + f"💡 提示: 每日签到(有效发言满 {MESSAGE_MIN_LENGTH} 字)获得 {MESSAGE_POINTS} 积分，" + f"每日上限 {MESSAGE_DAILY_CAP} 分。" ) bot.reply_to(message, welcome_text, parse_mode="HTML") @@ -93,44 +93,44 @@ def start_bot(): def get_chat_id(message): bot.reply_to( message, - f"馃幆 褰撳墠鑱婂ぉ鐨?Chat ID 鏄? {message.chat.id}", + f"🎯 当前聊天的 Chat ID 是: {message.chat.id}", parse_mode="HTML", ) @bot.message_handler(commands=["top"]) def show_points(message): - """鏄剧ず褰撳墠鐢ㄦ埛鐨勭Н鍒嗗強鎺掕姒?"" + """显示当前用户的积分及排行榜""" user = message.from_user db.upsert_user(user.id, _display_name(user)) user_info = db.get_user(user.id) leaderboard = db.get_leaderboard(limit=5) - rank_text = "馃弳 PolyWeather 娲昏穬搴︽帓琛屾\n" - rank_text += "鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€\n" + rank_text = "🏆 PolyWeather 活跃度排行榜\n" + rank_text += "────────────────────\n" for i, entry in enumerate(leaderboard): - medal = ["馃", "馃", "馃", " ", " "][i] if i < 5 else " " - rank_text += f"{medal} {entry['username'][:12]}: {entry['points']} 鐐筡n" + medal = ["🥇", "🥈", "🥉", " ", " "][i] if i < 5 else " " + rank_text += f"{medal} {entry['username'][:12]}: {entry['points']} 点\n" if user_info: - rank_text += "鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€鈹€\n" + rank_text += "────────────────────\n" rank_text += ( - f"馃懁 鎴戠殑鐘舵€侊細\n" - f"鈹?绉垎: {user_info['points']}\n" - f"鈹?鍙戣█: {user_info['message_count']} 娆n" - f"鈹?浠婃棩鍙戣█绉垎: {user_info.get('daily_points') or 0}/{MESSAGE_DAILY_CAP}\n" - f"鈹?/city 娑堣€? {CITY_QUERY_COST} | /deb 娑堣€? {DEB_QUERY_COST}" + f"👤 我的状态：\n" + f"┣ 积分: {user_info['points']}\n" + f"┣ 发言: {user_info['message_count']} 次\n" + f"┣ 今日发言积分: {user_info.get('daily_points') or 0}/{MESSAGE_DAILY_CAP}\n" + f"┗ /city 消耗: {CITY_QUERY_COST} | /deb 消耗: {DEB_QUERY_COST}" ) bot.send_message(message.chat.id, rank_text, parse_mode="HTML") @bot.message_handler(commands=["deb"]) def deb_accuracy(message): - """鏌ヨ DEB 铻嶅悎棰勬祴鐨勮繎 7 澶╁噯纭巼銆?"" + """查询 DEB 融合预测的近 7 天准确率。""" try: parts = message.text.split(maxsplit=1) if len(parts) < 2: bot.reply_to( message, - "鉂?鐢ㄦ硶: /deb ankara", + "❌ 用法: /deb ankara", parse_mode="HTML", ) return @@ -151,7 +151,7 @@ def start_bot(): if city_name not in data or not data[city_name]: bot.reply_to( message, - f"鉂?鏆傛棤 {city_name} 鐨勫巻鍙叉暟鎹€?, + f"❌ 暂无 {city_name} 的历史数据。", parse_mode="HTML", ) return @@ -176,9 +176,9 @@ def start_bot(): recent_items.sort(key=lambda item: item[0]) lines = [ - f"馃搳 DEB 鍑嗙‘鐜囨姤鍛?- {city_name.title()}", + f"📊 DEB 准确率报告 - {city_name.title()}", "", - "馃搮 杩?鏃ヨ褰曪細", + "📅 近日记录：", ] total_days = 0 hits = 0 @@ -209,7 +209,7 @@ def start_bot(): actual_wu = round(actual) if date_str == today_str: - lines.append(f" {date_str}: 馃搷 浠婂ぉ杩涜涓?(瀹炴祴鏆?{actual:.1f})") + lines.append(f" {date_str}: 📍 今天进行中 (实测暂 {actual:.1f})") elif deb_pred is not None: total_days += 1 deb_wu = round(deb_pred) @@ -221,18 +221,18 @@ def start_bot(): signed_errors.append(err) if hit: - result_icon = "鉁? - err_text = f"鍋忓樊{abs(err):.1f}掳" + result_icon = "✅" + err_text = f"偏差{abs(err):.1f}°" elif err < 0: - result_icon = "鉂? - err_text = f"浣庝及{abs(err):.1f}掳" + result_icon = "❌" + err_text = f"低估{abs(err):.1f}°" else: - result_icon = "鉂? - err_text = f"楂樹及{abs(err):.1f}掳" + result_icon = "❌" + err_text = f"高估{abs(err):.1f}°" - retro = "鈮? if "deb_prediction" not in record else "" + retro = "≈" if "deb_prediction" not in record else "" lines.append( - f" {date_str}: DEB {retro}{deb_pred:.1f}鈫抺deb_wu} vs 瀹炴祴 {actual:.1f}鈫抺actual_wu} " + f" {date_str}: DEB {retro}{deb_pred:.1f}→{deb_wu} vs 实测 {actual:.1f}→{actual_wu} " f"{result_icon} {err_text}" ) @@ -250,18 +250,18 @@ def start_bot(): deb_mae = sum(deb_errors) / len(deb_errors) lines.append("") lines.append( - f"馃幆 DEB 鎬绘垬缁╋細WU鍛戒腑 {hits}/{total_days} ({hit_rate:.0f}%) | MAE: {deb_mae:.1f}掳" + f"🏁 DEB 总战绩：WU命中 {hits}/{total_days} ({hit_rate:.0f}%) | MAE: {deb_mae:.1f}°" ) if model_errors: lines.append("") - lines.append("馃搱 妯″瀷 MAE 瀵规瘮锛?/b>") + lines.append("📈 模型 MAE 对比：") model_maes = {m: sum(e) / len(e) for m, e in model_errors.items() if e} sorted_models = sorted(model_maes.items(), key=lambda item: item[1]) for model, mae in sorted_models: - tag = " 猸? if mae <= deb_mae else "" - lines.append(f" {model}: {mae:.1f}掳{tag}") - lines.append(f" DEB铻嶅悎: {deb_mae:.1f}掳") + tag = " ⭐" if mae <= deb_mae else "" + lines.append(f" {model}: {mae:.1f}°{tag}") + lines.append(f" DEB融合: {deb_mae:.1f}°") mean_bias = sum(signed_errors) / len(signed_errors) underest = sum(1 for e in signed_errors if e < -0.3) @@ -269,55 +269,55 @@ def start_bot(): accurate = total_days - underest - overest lines.append("") - lines.append("馃攳 鍋忓樊鍒嗘瀽锛?/b>") + lines.append("🔍 偏差分析：") if abs(mean_bias) > 0.3: - bias_label = "绯荤粺鎬т綆浼? if mean_bias < 0 else "绯荤粺鎬ч珮浼? - lines.append(f" 鈿狅笍 {bias_label}锛氬钩鍧囧亸宸?{mean_bias:+.1f}掳") + bias_label = "系统性低估" if mean_bias < 0 else "系统性高估" + lines.append(f" ⚠️ {bias_label}：平均偏差 {mean_bias:+.1f}°") else: - lines.append(f" 鉁?鏁翠綋鏃犳槑鏄剧郴缁熷亸宸細骞冲潎鍋忓樊 {mean_bias:+.1f}掳") - lines.append(f" 浣庝及 {underest} 娆?| 楂樹及 {overest} 娆?| 鍑嗙‘ {accurate} 娆?) + lines.append(f" ✅ 整体无明显系统偏差：平均偏差 {mean_bias:+.1f}°") + lines.append(f" (低估 {underest} 次 | 高估 {overest} 次 | 准确 {accurate} 次)") lines.append("") - lines.append("馃挕 寤鸿锛?/b>") + lines.append("💡 建议：") if underest > overest and abs(mean_bias) > 0.5: lines.append( - f" 璇ュ煄甯傛ā鍨嬮泦浣撲綆浼拌秼鍔挎槑鏄撅紙{mean_bias:+.1f}掳锛夛紝瀹為檯鏈€楂樻俯鍙兘姣?DEB 铻嶅悎鍊奸珮 " - f"{abs(mean_bias):.0f}-{abs(mean_bias) + 0.5:.0f}掳銆備氦鏄撴椂寤鸿閫傚綋鐪嬮珮銆? + f" 该城市模型集体低估趋势明显（{mean_bias:+.1f}°），实际最高温可能比 DEB 融合值高 " + f"{abs(mean_bias):.0f}-{abs(mean_bias) + 0.5:.0f}°。交易时建议适当看高。" ) elif overest > underest and abs(mean_bias) > 0.5: lines.append( - f" 璇ュ煄甯傛ā鍨嬮泦浣撻珮浼拌秼鍔挎槑鏄撅紙{mean_bias:+.1f}掳锛夛紝瀹為檯鏈€楂樻俯鍙兘浣庝簬 DEB 铻嶅悎鍊笺€備氦鏄撴椂娉ㄦ剰杩介珮椋庨櫓銆? + f" 该城市模型集体高估趋势明显（{mean_bias:+.1f}°），实际最高温可能低于 DEB 融合值。交易时注意追高风险。" ) elif deb_mae > 1.5: - lines.append(f" 杩戞湡妯″瀷娉㈠姩杈冨ぇ锛圡AE {deb_mae:.1f}掳锛夛紝寤鸿闄嶄綆瀵瑰崟涓€鏃ラ娴嬬殑淇′换搴︺€?) + lines.append(f" 近期模型波动较大（MAE {deb_mae:.1f}°），建议降低对单一日预测的信任度。") elif hit_rate >= 60: - lines.append(" DEB 杩戞湡琛ㄧ幇绋冲畾锛屽彲缁х画浣滀负涓昏鍙傝€冦€?) + lines.append(" DEB 近期表现稳定，可继续作为主要参考。") else: - lines.append(" 杩戞湡鍑嗙‘鐜囦竴鑸紝寤鸿缁撳悎涓荤珯瀹炴祴涓庡懆杈圭珯鐐瑰叡鍚屽垽鏂€?) + lines.append(" 近期准确率一般，建议结合主站实测与周边站点共同判断。") lines.append("") - lines.append("馃摑 MAE = 骞冲潎缁濆璇樊锛岃秺灏忚秺鍑嗐€傗瓙 = 浼樹簬 DEB 铻嶅悎銆?) - lines.append("馃棑 缁熻绐楀彛锛氳繎7澶╂粴鍔ㄦ牱鏈€?) + lines.append("📝 MAE = 平均绝对误差，越小越准。⭐ = 优于 DEB 融合。") + lines.append("📅 统计窗口：近7天滚动样本。") else: lines.append("") - lines.append("鈴?杩?澶╁皻鏃犲畬鏁寸殑 DEB 棰勬祴璁板綍銆?) + lines.append("🔔 近 7 天尚无完整的 DEB 预测记录。") lines.append("") - lines.append(f"馃挸 鏈娑堣€?{DEB_QUERY_COST} 绉垎銆?) + lines.append(f"💸 本次消耗 {DEB_QUERY_COST} 积分。") bot.reply_to(message, "\n".join(lines), parse_mode="HTML") except Exception as e: - bot.reply_to(message, f"鉂?鏌ヨ澶辫触: {e}") + bot.reply_to(message, f"❌ 查询失败: {e}") @bot.message_handler(commands=["city"]) def get_city_info(message): - """鏌ヨ鎸囧畾鍩庡競鐨勫ぉ姘旇鎯?"" + """查询指定城市的天气详情""" try: parts = message.text.split(maxsplit=1) if len(parts) < 2: bot.reply_to( message, - "鉂?璇疯緭鍏ュ煄甯傚悕绉癨n\n鐢ㄦ硶: /city chicago", + "❌ 请输入城市名称\n\n用法: /city chicago", parse_mode="HTML", ) return @@ -325,35 +325,35 @@ def start_bot(): from src.data_collection.city_registry import ALIASES, CITY_REGISTRY city_input = parts[1].strip().lower() - # --- 浣跨敤缁熶竴娉ㄥ唽琛ㄨВ鏋愬煄甯?--- + # --- 使用统一注册表解析城市 --- SUPPORTED_CITIES = list(CITY_REGISTRY.keys()) - # 1. 绗竴浼樺厛绾э細鍏ㄧО鎴栧埆鍚嶅畬鍏ㄥ尮閰? + # 1. 第一优先级：全称或别名完全匹配 city_name = ALIASES.get(city_input) if not city_name and city_input in SUPPORTED_CITIES: city_name = city_input - # 2. 绗簩浼樺厛绾э細鍓嶇紑妯＄硦鍖归厤 + # 2. 第二优先级：前缀模糊匹配 if not city_name and len(city_input) >= 2: - # 鎼滃埆鍚? + # 搜别名 for k, v in ALIASES.items(): if k.startswith(city_input): city_name = v break - # 鎼滃煄甯傚叏鍚? + # 搜城市全名 if not city_name: for full_name in SUPPORTED_CITIES: if full_name.startswith(city_input): city_name = full_name break - # 3. 鏈壘鍒?鈫?鎶ラ敊 + # 3. 未找到 ➔ 报错 if not city_name: city_list = ", ".join(sorted(SUPPORTED_CITIES)) bot.reply_to( message, - f"鉂?鏈壘鍒板煄甯? {city_input}\n\n" - f"鏀寔鐨勫煄甯? {city_list}", + f"❌ 未找到城市: {city_input}\n\n" + f"支持的城市: {city_list}", parse_mode="HTML", ) return @@ -362,12 +362,12 @@ def start_bot(): return bot.send_message( - message.chat.id, f"馃攳 姝ｅ湪鏌ヨ {city_name.title()} 鐨勫ぉ姘旀暟鎹?.." + message.chat.id, f"🔍 正在查询 {city_name.title()} 的天气数据..." ) coords = weather.get_coordinates(city_name) if not coords: - bot.reply_to(message, f"鉂?鏈壘鍒板煄甯傚潗鏍? {city_name}") + bot.reply_to(message, f"❌ 未找到城市坐标: {city_name}") return weather_data = weather.fetch_all_sources( @@ -387,26 +387,26 @@ def start_bot(): return None temp_unit = open_meteo.get("unit", "celsius") - temp_symbol = "掳F" if temp_unit == "fahrenheit" else "掳C" + temp_symbol = "°F" if temp_unit == "fahrenheit" else "°C" - # --- 1. 绱у噾 Header (鍩庡競 + 鏃堕棿 + 椋庨櫓鐘舵€? --- + # --- 1. 紧凑 Header (城市 + 时间 + 风险状态) --- local_time = open_meteo.get("current", {}).get("local_time", "") time_str = local_time.split(" ")[1][:5] if " " in local_time else "N/A" risk_profile = get_city_risk_profile(city_name) - risk_emoji = risk_profile.get("risk_level", "鈿?) if risk_profile else "鈿? + risk_emoji = risk_profile.get("risk_level", "⚠️") if risk_profile else "⚠️" - msg_header = f"馃搷 {city_name.title()} ({time_str}) {risk_emoji}" + msg_header = f"📍 {city_name.title()} ({time_str}) {risk_emoji}" msg_lines = [msg_header] - # --- 2. 绱у噾 椋庨櫓鎻愮ず --- + # --- 2. 紧凑 风险提示 --- if risk_profile: - bias = risk_profile.get("bias", "卤0.0") + bias = risk_profile.get("bias", "±0.0") msg_lines.append( - f"鈿狅笍 {risk_profile.get('airport_name', '')}: {bias}{temp_symbol} | {risk_profile.get('warning', '')}" + f"⚠️ {risk_profile.get('airport_name', '')}: {bias}{temp_symbol} | {risk_profile.get('warning', '')}" ) - # --- 3. 绱у噾 棰勬祴鍖?--- + # --- 3. 紧凑 预测区 --- daily = open_meteo.get("daily", {}) dates = daily.get("time", [])[:3] max_temps = daily.get("temperature_2m_max", [])[:3] @@ -415,7 +415,7 @@ def start_bot(): mgm_high = _sf(mgm.get("today_high")) mb_high = _sf(weather_data.get("meteoblue", {}).get("today_high")) - # 浠婂ぉ瀵规瘮 + # 今天对比 today_t = max_temps[0] if max_temps else "N/A" comp_parts = [] sources = ["Open-Meteo"] @@ -437,45 +437,45 @@ def start_bot(): if mgm_high is not None: sources.append("MGM") comp_parts.append( - f"馃嚬馃嚪 MGM: {mgm_high:.1f}{temp_symbol}" + f"🇺🇸 MGM: {mgm_high:.1f}{temp_symbol}" if isinstance(mgm_high, (int, float)) - else f"馃嚬馃嚪 MGM: {mgm_high}" + else f"🇺🇸 MGM: {mgm_high}" ) - # 妫€鏌ユ槸鍚︽湁鏄捐憲鍒嗘 (瓒呰繃 5掳F 鎴?2.5掳C) + # 检查是否有显著分歧 (超过 5°F 或 2.5°C) divergence_warning = "" if mb_high is not None and max_temps: diff = abs(mb_high - (_sf(max_temps[0]) or 0)) threshold = 5.0 if temp_unit == "fahrenheit" else 2.5 if diff > threshold: divergence_warning = ( - f" 鈿狅笍 妯″瀷鏄捐憲鍒嗘 ({diff:.1f}{temp_symbol})" + f" ⚠️ 模型显著分歧 ({diff:.1f}{temp_symbol})" ) comp_str = f" ({' | '.join(comp_parts)})" if comp_parts else "" sources_str = " | ".join(sources) - msg_lines.append(f"\n馃搳 棰勬姤 ({sources_str})") + msg_lines.append(f"\n📊 预报 ({sources_str})") msg_lines.append( - f"馃憠 浠婂ぉ: {today_t}{temp_symbol}{comp_str}{divergence_warning}" + f"👉 今天: {today_t}{temp_symbol}{comp_str}{divergence_warning}" ) - # 鏄庡悗澶? + # 明后天 if len(dates) > 1: future_forecasts = [] mgm_daily = mgm.get("daily_forecasts", {}) or {} for d, t in zip(dates[1:], max_temps[1:]): - # 妫€鏌?MGM 鏄惁鏈夎鏃ユ湡鐨勯鎶? + # 检查 MGM 是否有该日期的预报 mgm_f = mgm_daily.get(d) if mgm_f is not None: future_forecasts.append( - f"{d[5:]}: {t}{temp_symbol} | 馃嚬馃嚪 MGM: {mgm_f}{temp_symbol}" + f"{d[5:]}: {t}{temp_symbol} | 🇺🇸 MGM: {mgm_f}{temp_symbol}" ) else: future_forecasts.append(f"{d[5:]}: {t}{temp_symbol}") - msg_lines.append("馃搮 " + " | ".join(future_forecasts)) + msg_lines.append("📅 " + " | ".join(future_forecasts)) - # --- 3.5 鏃ュ嚭鏃ヨ惤 + 鏃ョ収鏃堕暱 --- + # --- 3.5 日出日落 + 日照时长 --- sunrises = daily.get("sunrise", []) sunsets = daily.get("sunset", []) sunshine_durations = daily.get("sunshine_duration", []) @@ -490,14 +490,14 @@ def start_bot(): if "T" in str(sunsets[0]) else sunsets[0] ) - sun_line = f"馃寘 鏃ュ嚭 {sunrise_t} | 馃寚 鏃ヨ惤 {sunset_t}" + sun_line = f"🌅 日出 {sunrise_t} | 🌇 日落 {sunset_t}" if sunshine_durations: - sunshine_hours = sunshine_durations[0] / 3600 # 绉?-> 灏忔椂 - sun_line += f" | 鈽€锔?鏃ョ収 {sunshine_hours:.1f}h" + sunshine_hours = sunshine_durations[0] / 3600 # 秒 -> 小时 + sun_line += f" | ☀️ 日照 {sunshine_hours:.1f}h" msg_lines.append(sun_line) - # --- 4. 鏍稿績 瀹炴祴鍖?(鍚堝苟 METAR 鍜?MGM) --- - # 鍩虹鏁版嵁浼樺厛鐢?METAR + # --- 4. 核心 实测区 (合并 METAR 和 MGM) --- + # 基础数据优先用 METAR cur_temp = _sf( metar.get("current", {}).get("temp") if metar @@ -510,7 +510,7 @@ def start_bot(): metar.get("current", {}).get("max_temp_time") if metar else None ) obs_t_str = "N/A" - metar_age_min = None # METAR 鏁版嵁骞撮緞锛堝垎閽燂級 + metar_age_min = None # METAR 数据年龄（分钟） main_source = "METAR" if metar else "MGM" if metar: @@ -525,7 +525,7 @@ def start_bot(): timezone(timedelta(seconds=utc_offset)) ) obs_t_str = local_dt.strftime("%H:%M") - # 璁＄畻鏁版嵁骞撮緞 + # 计算数据年龄 now_utc = datetime.now(timezone.utc) metar_age_min = int((now_utc - dt).total_seconds() / 60) elif " " in obs_t: @@ -547,27 +547,27 @@ def start_bot(): m_time = m_time.split(" ")[1][:5] obs_t_str = m_time - # 鏁版嵁骞撮緞鏍囨敞 + # 数据年龄标注 age_tag = "" if metar_age_min is not None: if metar_age_min >= 60: - age_tag = f" 鈿狅笍{metar_age_min}鍒嗛挓鍓? + age_tag = f" ⚠️{metar_age_min}分钟前" elif metar_age_min >= 30: - age_tag = f" 鈴硔metar_age_min}鍒嗛挓鍓? + age_tag = f" 🔔{metar_age_min}分钟前" max_str = "" if max_p is not None: import math settled_val = math.floor(max_p + 0.5) - max_str = f" (鏈€楂? {max_p}{temp_symbol}" + max_str = f" (最高: {max_p}{temp_symbol}" if max_p_time: max_str += f" @{max_p_time}" - max_str += f" 鈫?WU {settled_val}{temp_symbol})" + max_str += f" → WU {settled_val}{temp_symbol})" - # --- 澶╂皵鐘跺喌鎬荤粨 --- + # --- 天气状况总结 --- wx_summary = "" - # 浼樺厛浣跨敤 METAR 澶╂皵鐜拌薄 + # 优先使用 METAR 天气现象 metar_wx = metar.get("current", {}).get("wx_desc", "") if metar else "" metar_clouds = metar.get("current", {}).get("clouds", []) if metar else [] mgm_cloud = mgm.get("current", {}).get("cloud_cover") if mgm else None @@ -590,21 +590,21 @@ def start_bot(): fog_codes = {"FG", "BR", "HZ", "FZFG"} ts_codes = {"TS", "TSRA"} if ts_codes & wx_tokens: - wx_summary = "鉀堬笍 闆锋毚" + wx_summary = "⛈️ 雷暴" elif {"+RA", "+SN"} & wx_tokens: - wx_summary = "馃導锔?澶ч洦" if "+RA" in wx_tokens else "鉂勶笍 澶ч洩" + wx_summary = "🌧️ 大雨" if "+RA" in wx_tokens else "❄️ 大雪" elif rain_codes & wx_tokens: wx_summary = ( - "馃導锔?灏忛洦" if {"-RA", "-DZ", "DZ"} & wx_tokens else "馃導锔?涓嬮洦" + "🌧️ 小雨" if {"-RA", "-DZ", "DZ"} & wx_tokens else "🌧️ 下雨" ) elif snow_codes & wx_tokens: - wx_summary = "鉂勶笍 涓嬮洩" + wx_summary = "❄️ 下雪" elif fog_codes & wx_tokens: - wx_summary = "馃尗锔?闆?闇? + wx_summary = "🌫️ 雾 / 霾" - # 濡傛灉 METAR 娌℃湁鐗规畩鐜拌薄锛岀敤浜戦噺鎺ㄦ柇 + # 如果 METAR 没有特殊现象，用云量推断 if not wx_summary: - # 浼樺厛 METAR 浜戝眰锛屽洖閫€ MGM + # 优先 METAR 云层，回退 MGM cover_code = "" if metar_clouds: cover_code = metar_clouds[-1].get("cover", "") @@ -612,98 +612,98 @@ def start_bot(): if cover_code in ("SKC", "CLR") or ( cover_code == "" and mgm_cloud is not None and mgm_cloud <= 1 ): - wx_summary = "鈽€锔?鏅? + wx_summary = "☀️ 晴" elif cover_code == "FEW" or ( cover_code == "" and mgm_cloud is not None and mgm_cloud <= 2 ): - wx_summary = "馃尋锔?鏅撮棿灏戜簯" + wx_summary = "🌤️ 晴间少云" elif cover_code == "SCT" or ( cover_code == "" and mgm_cloud is not None and mgm_cloud <= 4 ): - wx_summary = "鉀?鏅撮棿澶氫簯" + wx_summary = "⛅ 晴间多云" elif cover_code == "BKN" or ( cover_code == "" and mgm_cloud is not None and mgm_cloud <= 6 ): - wx_summary = "馃尌锔?澶氫簯" + wx_summary = "🌥️ 多云" elif cover_code == "OVC" or ( cover_code == "" and mgm_cloud is not None and mgm_cloud <= 8 ): - wx_summary = "鈽侊笍 闃村ぉ" + wx_summary = "☁️ 阴天" elif mgm_cloud is not None: cloud_names = { - 0: "鈽€锔?鏅?, - 1: "馃尋锔?鏅?, - 2: "馃尋锔?灏戜簯", - 3: "鉀?鏁ｄ簯", - 4: "鉀?鏁ｄ簯", - 5: "馃尌锔?澶氫簯", - 6: "馃尌锔?澶氫簯", - 7: "鈽侊笍 闃?, - 8: "鈽侊笍 闃村ぉ", + 0: "☀️ 晴", + 1: "☀️ 晴", + 2: "🌤️ 少云", + 3: "⛅ 散云", + 4: "⛅ 散云", + 5: "🌥️ 多云", + 6: "🌥️ 多云", + 7: "☁️ 阴", + 8: "☁️ 阴天", } wx_summary = cloud_names.get(mgm_cloud, "") wx_display = f" {wx_summary}" if wx_summary else "" msg_lines.append( - f"\n鉁堬笍 瀹炴祴 ({main_source}): {cur_temp}{temp_symbol}{max_str} |{wx_display} | {obs_t_str}{age_tag}" + f"\n✈️ 实测 ({main_source}): {cur_temp}{temp_symbol}{max_str} |{wx_display} | {obs_t_str}{age_tag}" ) if mgm: m_c = mgm.get("current", {}) - # 缈昏瘧椋庡悜 + # 翻译风向 wind_dir = m_c.get("wind_dir") wind_speed_ms = m_c.get("wind_speed_ms") dir_str = "" if wind_dir is not None: - dirs = ["鍖?, "涓滃寳", "涓?, "涓滃崡", "鍗?, "瑗垮崡", "瑗?, "瑗垮寳"] - dir_str = dirs[int((float(wind_dir) + 22.5) % 360 / 45)] + "椋?" + dirs = ["北", "东北", "东", "东南", "南", "西南", "西", "西北"] + dir_str = dirs[int((float(wind_dir) + 22.5) % 360 / 45)] + "风" - # 浣撴劅鍜屾箍搴︼紙璺宠繃缂哄け鏁版嵁锛? + # 体感和湿度（跳过缺失数据） feels_like = m_c.get("feels_like") humidity = m_c.get("humidity") if feels_like is not None or humidity is not None: parts = [] if feels_like is not None: - parts.append(f"馃尅锔?浣撴劅: {feels_like}掳C") + parts.append(f"🌡️ 体感: {feels_like}°C") - # 閽堝瀹夊崱鎷夛紝琛ュ厖甯傚尯(Center)瀹炴祴鍊? - ankara_center = next((s for s in weather_data.get("mgm_nearby", []) if "B枚lge/Center" in s.get("name", "")), None) + # 针对安卡拉，补充市区(Center)实测值 + ankara_center = next((s for s in weather_data.get("mgm_nearby", []) if "Bölge/Center" in s.get("name", "")), None) if ankara_center: - parts.append(f"Ankara (B枚lge/Center): {ankara_center['temp']}掳C") + parts.append(f"Ankara (Bölge/Center): {ankara_center['temp']}°C") if humidity is not None: - parts.append(f"馃挧 {humidity}%") + parts.append(f"💧 {humidity}%") msg_lines.append(f" [MGM] {' | '.join(parts)}") - # 椋庡喌锛堣烦杩囩己澶辨暟鎹級 + # 风况（跳过缺失数据） if wind_dir is not None and wind_speed_ms is not None: msg_lines.append( - f" [MGM] 馃尙锔?{dir_str}{wind_dir}掳 ({wind_speed_ms} m/s) | 馃挧 闄嶆按: {m_c.get('rain_24h') or 0}mm" + f" [MGM] 🌬️ {dir_str}{wind_dir}° ({wind_speed_ms} m/s) | 💧 降水: {m_c.get('rain_24h') or 0}mm" ) - # 鏂板锛氭皵鍘嬪拰浜戦噺 + # 新增：气压和云量 extra_parts = [] pressure = m_c.get("pressure") if pressure is not None: - extra_parts.append(f"馃尅 姘斿帇: {pressure}hPa") + extra_parts.append(f"🌡 气压: {pressure}hPa") cloud_cover = m_c.get("cloud_cover") if cloud_cover is not None: cloud_desc_map = { - 0: "鏅存湕", - 1: "灏戜簯", - 2: "灏戜簯", - 3: "鏁ｄ簯", - 4: "鏁ｄ簯", - 5: "澶氫簯", - 6: "澶氫簯", - 7: "寰堝浜?, - 8: "闃村ぉ", + 0: "晴朗", + 1: "少云", + 2: "少云", + 3: "散云", + 4: "散云", + 5: "多云", + 6: "多云", + 7: "很多云", + 8: "阴天", } cloud_text = cloud_desc_map.get(cloud_cover, f"{cloud_cover}/8") - extra_parts.append(f"鈽侊笍 浜戦噺: {cloud_text}({cloud_cover}/8)") + extra_parts.append(f"☁️ 云量: {cloud_text}({cloud_cover}/8)") mgm_max = m_c.get("mgm_max_temp") if mgm_max is not None: - extra_parts.append(f"馃尅锔?MGM鏈€楂? {mgm_max}掳C") + extra_parts.append(f"🌡️ MGM最高: {mgm_max}°C") if extra_parts: msg_lines.append(f" [MGM] {' | '.join(extra_parts)}") @@ -717,45 +717,45 @@ def start_bot(): cloud_desc = "" if clouds: c_map = { - "BKN": "澶氫簯", - "OVC": "闃村ぉ", - "FEW": "灏戜簯", - "SCT": "鏁ｄ簯", - "SKC": "鏅?, - "CLR": "鏅?, + "BKN": "多云", + "OVC": "阴天", + "FEW": "少云", + "SCT": "散云", + "SKC": "晴", + "CLR": "晴", } main = clouds[-1] - cloud_desc = f"鈽侊笍 {c_map.get(main.get('cover'), main.get('cover'))}" + cloud_desc = f"☁️ {c_map.get(main.get('cover'), main.get('cover'))}" prefix = "[METAR]" if mgm else " " if not mgm: msg_lines.append( - f" {prefix} 馃挩 {wind or 0}kt ({wind_dir or 0}掳) | 馃憗锔?{vis or 10}mi" + f" {prefix} 🌪 {wind or 0}kt ({wind_dir or 0}°) | 👁️ {vis or 10}mi" ) if cloud_desc: msg_lines.append( - f" {prefix} {cloud_desc} | 馃憗锔?{vis or 10}mi | 馃挩 {wind or 0}kt" + f" {prefix} {cloud_desc} | 👁️ {vis or 10}mi | 🌪 {wind or 0}kt" ) - # --- 5. 鎬佸娍鐗瑰緛鎻愬彇 --- + # --- 5. 态势特征提取 --- feature_str, ai_context = analyze_weather_trend( weather_data, temp_symbol, city_name ) if feature_str: - # 浠呭皢鏈€鏍稿績鐨勪俊鎭睍绀虹粰鐢ㄦ埛浣滀负"鎬佸娍鍒嗘瀽" - # 浣嗗悗闈細鎶婃洿鍏ㄧ殑鏁版嵁浼犵粰 AI - msg_lines.append("\n馃挕 鍒嗘瀽:") + # 仅将最核心的信息展示给用户作为"态势分析" + # 但后面会把更全的数据传给 AI + msg_lines.append("\n💡 分析:") for line in feature_str.split("\n"): if line.strip(): msg_lines.append(f"- {line.strip()}") - # --- 6. Groq AI 娣卞害鍒嗘瀽 --- + # --- 6. Groq AI 深度分析 --- try: from src.analysis.ai_analyzer import get_ai_analysis - # 鏋勫缓鏇村叏鐨勮儗鏅暟鎹粰 AI + # 构建更全的背景数据给 AI - # 琛ュ厖澶氭ā鍨嬪垎姝? + # 补充多模型分歧 mm = weather_data.get("multi_model", {}) if mm.get("forecasts"): mm_str = " | ".join( @@ -765,26 +765,26 @@ def start_bot(): if v ] ) - ai_context += f"\n妯″瀷鍒嗘: {mm_str}" + ai_context += f"\n模型分歧: {mm_str}" ai_result = get_ai_analysis(ai_context, city_name, temp_symbol) if ai_result: msg_lines.append(f"\n{ai_result}") except Exception as e: - logger.error(f"璋冪敤 Groq AI 鍒嗘瀽澶辫触: {e}") + logger.error(f"调用 Groq AI 分析失败: {e}") - msg_lines.append(f"\n馃挸 鏈娑堣€?{CITY_QUERY_COST} 绉垎銆?) + msg_lines.append(f"\n💸 本次消耗 {CITY_QUERY_COST} 积分。") bot.send_message(message.chat.id, "\n".join(msg_lines), parse_mode="HTML") except Exception as e: import traceback - logger.error(f"鏌ヨ澶辫触: {e}\n{traceback.format_exc()}") - bot.reply_to(message, f"鉂?鏌ヨ澶辫触: {e}") + logger.error(f"查询失败: {e}\n{traceback.format_exc()}") + bot.reply_to(message, f"❌ 查询失败: {e}") @bot.message_handler(func=lambda message: True, content_types=['text']) def track_activity(message): - """鍏ㄩ噺鐩戝惉娑堟伅锛岀敤浜庤褰曠兢鍐呭彂瑷€绉垎(闈炴寚浠ゆ秷鎭?""" + """全量监听消息，用于记录群内发言积分(非指令消息)""" if message.text.startswith('/'): return if message.chat.type not in ("group", "supergroup"): @@ -808,7 +808,7 @@ def start_bot(): f"daily_points={result.get('daily_points')}/{MESSAGE_DAILY_CAP}" ) - logger.info("馃 Bot 鍚姩涓?..") + logger.info("🤖 Bot 启动中...") bot.infinity_polling()