feat: Introduce a web frontend with new city API routes and refactor bot city query logic into a dedicated service.

.env.example

@@ -30,6 +30,9 @@ HTTP_PROXY=http://127.0.0.1:7890
 LOG_LEVEL=INFO
 ENV=production
 POLYWEATHER_MAP_URL=https://polyweather-pro.vercel.app/
+# Backend entitlement guard (for /api/cities, /api/city/*, /api/history/*)
+POLYWEATHER_REQUIRE_ENTITLEMENT=false
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=
 
 # Polymarket P0 Read-Only Market Layer
 POLYMARKET_MARKET_SCAN_ENABLED=true
@@ -74,4 +77,3 @@ POLYMARKET_WALLET_ACTIVITY_BOOTSTRAP_ALERT=false
 POLYMARKET_WALLET_ACTIVITY_AVG_PRICE_SHOW_MIN=0.01
 POLYMARKET_WALLET_ACTIVITY_AVG_PRICE_SHOW_MAX=0.99
 
-

bot_listener.py

@@ -1,6 +1,5 @@
 import sys
 import os
-from typing import List
 import telebot  # type: ignore
 from loguru import logger  # type: ignore
 
@@ -14,10 +13,11 @@ from src.utils.telegram_push import start_trade_alert_push_loop  # type: ignore
 from src.onchain.polygon_wallet_watcher import start_polygon_wallet_watch_loop  # type: ignore # noqa: E402
 from src.onchain.polymarket_wallet_activity_watcher import start_polymarket_wallet_activity_loop  # type: ignore # noqa: E402
 from src.data_collection.weather_sources import WeatherDataCollector  # type: ignore # noqa: E402
-from src.data_collection.city_registry import CITY_REGISTRY  # noqa: E402
-from src.data_collection.city_risk_profiles import get_city_risk_profile  # type: ignore # noqa: E402
-from src.analysis.deb_algorithm import calculate_dynamic_weights, update_daily_record  # noqa: E402
 from src.database.db_manager import DBManager
+from src.analysis.city_query_service import (
+    resolve_city_name,
+    build_city_query_report,
+)
 
 MESSAGE_POINTS = 4
 MESSAGE_DAILY_CAP = 50
@@ -27,13 +27,6 @@ CITY_QUERY_COST = 1
 DEB_QUERY_COST = 1
 
 
-def analyze_weather_trend(weather_data, temp_symbol, city_name=None):
-    """Thin wrapper 鈥?delegates to shared trend_engine module."""
-    from src.analysis.trend_engine import analyze_weather_trend as _analyze
-    display_str, ai_context, _structured = _analyze(weather_data, temp_symbol, city_name)
-    return display_str, ai_context
-
-
 def start_bot():
     config = load_config()
     token = os.getenv("TELEGRAM_BOT_TOKEN")
@@ -310,7 +303,6 @@ def start_bot():
             bot.reply_to(message, f"❌ 查询失败: {e}")
 
     @bot.message_handler(commands=["city"])
-
     def get_city_info(message):
         """查询指定城市的天气详情"""
         try:
@@ -323,38 +315,13 @@ def start_bot():
                 )
                 return
 
-            from src.data_collection.city_registry import ALIASES, CITY_REGISTRY
             city_input = parts[1].strip().lower()
-            
+            city_name, supported_cities = resolve_city_name(city_input)
-            # --- 使用统一注册表解析城市 ---
-            SUPPORTED_CITIES = list(CITY_REGISTRY.keys())
-
-            # 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. 第二优先级：前缀模糊匹配
-            if not city_name and len(city_input) >= 2:
-                # 搜别名
-                for k, v in ALIASES.items():
-                    if k.startswith(city_input):
-                        city_name = v
-                        break
-                # 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. 未找到 ➔ 报错
             if not city_name:
-                city_list = ", ".join(sorted(SUPPORTED_CITIES))
+                city_list = ", ".join(supported_cities)
                 bot.reply_to(
                     message,
-                    f"❌ 未找到城市: <b>{city_input}</b>\n\n"
+                    f"❌ 未找到城市: <b>{city_input}</b>\n\n支持的城市: {city_list}",
-                    f"支持的城市: {city_list}",
                     parse_mode="HTML",
                 )
                 return
@@ -374,586 +341,12 @@ def start_bot():
             weather_data = weather.fetch_all_sources(
                 city_name, lat=coords["lat"], lon=coords["lon"]
             )
-            open_meteo = weather_data.get("open-meteo", {})
+            city_report = build_city_query_report(
-            metar = weather_data.get("metar", {})
+                city_name=city_name,
-            mgm = weather_data.get("mgm") or {}
+                weather_data=weather_data,
-            city_meta = CITY_REGISTRY.get(city_name.lower(), {})
+                city_query_cost=CITY_QUERY_COST,
-            fallback_utc_offset = int(city_meta.get("tz_offset", 0))
-            nws_periods = (weather_data.get("nws", {}) or {}).get("forecast_periods", []) or []
-            if nws_periods:
-                try:
-                    from datetime import datetime as _dt
-
-                    first_start = nws_periods[0].get("start_time")
-                    if first_start:
-                        maybe_dt = _dt.fromisoformat(str(first_start))
-                        if maybe_dt.utcoffset() is not None:
-                            fallback_utc_offset = int(maybe_dt.utcoffset().total_seconds())
-                except Exception:
-                    pass
-
-            # 鏁板€煎綊涓€鍖?
-            def _sf(v):
-                if v is None:
-                    return None
-                try:
-                    return float(v)
-                except Exception:
-                    return None
-
-            city_is_fahrenheit = city_name.strip().lower() in ["dallas", "new york", "chicago", "miami", "atlanta", "seattle"]
-            temp_symbol = "°F" if city_is_fahrenheit else "°C"
-
-            # --- 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"
-            if time_str == "N/A":
-                metar_obs = metar.get("observation_time", "") if metar else ""
-                if "T" in metar_obs:
-                    try:
-                        from datetime import datetime, timezone, timedelta
-
-                        dt = datetime.fromisoformat(metar_obs.replace("Z", "+00:00"))
-                        utc_offset_for_view = open_meteo.get("utc_offset")
-                        if utc_offset_for_view is None:
-                            utc_offset_for_view = fallback_utc_offset
-                        local_dt = dt.astimezone(
-                            timezone(timedelta(seconds=int(utc_offset_for_view)))
-                        )
-                        time_str = local_dt.strftime("%H:%M")
-                    except Exception:
-                        time_str = metar_obs.split("T")[1][:5]
-                elif " " in metar_obs:
-                    time_str = metar_obs.split(" ")[1][:5]
-                elif metar_obs:
-                    time_str = str(metar_obs)[:5]
-                else:
-                    try:
-                        from datetime import datetime, timezone, timedelta
-
-                        local_now = datetime.now(timezone.utc).astimezone(
-                            timezone(timedelta(seconds=int(fallback_utc_offset)))
-                        )
-                        time_str = local_now.strftime("%H:%M")
-                    except Exception:
-                        pass
-
-            risk_profile = get_city_risk_profile(city_name)
-            risk_emoji = risk_profile.get("risk_level", "⚠️") if risk_profile else "⚠️"
-
-            msg_header = f"📍 <b>{city_name.title()}</b> ({time_str}) {risk_emoji}"
-            msg_lines = [msg_header]
-
-            # --- 2. 紧凑 风险提示 ---
-            if risk_profile:
-                bias = risk_profile.get("bias", "±0.0")
-                msg_lines.append(
-                    f"⚠️ {risk_profile.get('airport_name', '')}: {bias}{temp_symbol} | {risk_profile.get('warning', '')}"
-                )
-
-            # --- 3. 紧凑 预测区 ---
-            daily = open_meteo.get("daily", {})
-            dates = daily.get("time", [])[:3]
-            max_temps = daily.get("temperature_2m_max", [])[:3]
-
-            nws_high = _sf(weather_data.get("nws", {}).get("today_high"))
-            mgm_high = _sf(mgm.get("today_high"))
-            mb_high = _sf(weather_data.get("meteoblue", {}).get("today_high"))
-            metar_max_so_far = _sf(metar.get("current", {}).get("max_temp_so_far")) if metar else None
-
-            # 今天对比
-            today_t = _sf(max_temps[0]) if max_temps else None
-            fallback_source = None
-            metar_only_fallback = False
-            if today_t is None:
-                for source_name, candidate in (
-                    ("MB", mb_high),
-                    ("NWS", nws_high),
-                    ("MGM", mgm_high),
-                ):
-                    if candidate is not None:
-                        today_t = candidate
-                        fallback_source = source_name
-                        break
-            if today_t is None and metar_max_so_far is not None:
-                # Last-resort display only: do not treat METAR as a forecast source
-                today_t = metar_max_so_far
-                metar_only_fallback = True
-            today_t_display = (
-                f"{today_t:.1f}" if isinstance(today_t, (int, float)) else "N/A"
             )
-            comp_parts = []
+            bot.send_message(message.chat.id, city_report, parse_mode="HTML")
-            sources = ["Open-Meteo"] if max_temps else []
-
-            if mb_high is not None:
-                if "MB" not in sources:
-                    sources.append("MB")
-                # 只在非 fallback（即 Open-Meteo 存在）时显示为对比，否则作为 today_t 已显示
-                if fallback_source != "MB":
-                    comp_parts.append(
-                        f"MB: {mb_high:.1f}{temp_symbol}"
-                        if isinstance(mb_high, (int, float))
-                        else f"MB: {mb_high}"
-                    )
-            if nws_high is not None:
-                if "NWS" not in sources:
-                    sources.append("NWS")
-                if fallback_source != "NWS":
-                    comp_parts.append(
-                        f"NWS: {nws_high:.1f}{temp_symbol}"
-                        if isinstance(nws_high, (int, float))
-                        else f"NWS: {nws_high}"
-                    )
-            if mgm_high is not None:
-                if "MGM" not in sources:
-                    sources.append("MGM")
-                if fallback_source != "MGM":
-                    comp_parts.append(
-                        f"MGM: {mgm_high:.1f}{temp_symbol}"
-                        if isinstance(mgm_high, (int, float))
-                        else f"MGM: {mgm_high}"
-                    )
-            if fallback_source and fallback_source not in sources:
-                sources.append(fallback_source)
-            if metar_only_fallback:
-                if not sources:
-                    sources = ["Model unavailable"]
-                comp_parts.append(f"METAR实测回退: {metar_max_so_far:.1f}{temp_symbol}")
-            if not sources:
-                sources = ["N/A"]
-
-            # 检查是否有显著分歧 (超过 5°F 或 2.5°C)
-            divergence_warning = ""
-            base_for_divergence = _sf(max_temps[0]) if max_temps else today_t
-            if mb_high is not None and base_for_divergence is not None:
-                diff = abs(mb_high - base_for_divergence)
-                threshold = 5.0 if temp_unit == "fahrenheit" else 2.5
-                if diff > threshold:
-                    divergence_warning = (
-                        f" ⚠️ <b>模型显著分歧 ({diff:.1f}{temp_symbol})</b>"
-                    )
-
-            comp_str = f" ({' | '.join(comp_parts)})" if comp_parts else ""
-            sources_str = " | ".join(sources)
-
-            msg_lines.append(f"\n📊 <b>预报 ({sources_str})</b>")
-            msg_lines.append(
-                f"👉 <b>今天: {today_t_display}{temp_symbol}{comp_str}</b>{divergence_warning}"
-            )
-
-            # 明后天
-            mgm_daily = mgm.get("daily_forecasts", {}) or {}
-            mm_raw = weather_data.get("multi_model", {}) or {}
-            mm_daily = mm_raw.get("daily_forecasts", {}) if isinstance(mm_raw, dict) else {}
-            mb_daily = weather_data.get("meteoblue", {}).get("daily_highs", []) or []
-            nws_periods = weather_data.get("nws", {}).get("forecast_periods", []) or []
-            if len(dates) > 1:
-                future_forecasts = []
-                for d, t in zip(dates[1:], max_temps[1:]):
-                    # 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} | 🇺🇸 <b>MGM: {mgm_f}{temp_symbol}</b>"
-                        )
-                    else:
-                        future_forecasts.append(f"{d[5:]}: {t}{temp_symbol}")
-                msg_lines.append("📅 " + " | ".join(future_forecasts))
-            elif mgm_daily:
-                # Open-Meteo missing: still show next 2 days from MGM daily forecast
-                from datetime import datetime, timezone, timedelta
-
-                local_now = datetime.now(timezone.utc).astimezone(
-                    timezone(timedelta(seconds=int(fallback_utc_offset)))
-                )
-                today_local = local_now.strftime("%Y-%m-%d")
-                future_forecasts = []
-                for d in sorted(mgm_daily.keys()):
-                    if d <= today_local:
-                        continue
-                    t = mgm_daily.get(d)
-                    if t is None:
-                        continue
-                    future_forecasts.append(f"{d[5:]}: {t}{temp_symbol}")
-                    if len(future_forecasts) >= 2:
-                        break
-                if future_forecasts:
-                    msg_lines.append("📅 " + " | ".join(future_forecasts))
-            elif isinstance(mm_daily, dict) and mm_daily:
-                # Open-Meteo missing: fallback to multi-model daily medians
-                from datetime import datetime, timezone, timedelta
-
-                local_now = datetime.now(timezone.utc).astimezone(
-                    timezone(timedelta(seconds=int(fallback_utc_offset)))
-                )
-                today_local = local_now.strftime("%Y-%m-%d")
-                future_forecasts = []
-                for d in sorted(mm_daily.keys()):
-                    if d <= today_local:
-                        continue
-                    day_models = mm_daily.get(d, {}) or {}
-                    vals = []
-                    for v in day_models.values():
-                        vv = _sf(v)
-                        if vv is not None:
-                            vals.append(vv)
-                    if not vals:
-                        continue
-                    vals.sort()
-                    median_v = vals[len(vals) // 2]
-                    future_forecasts.append(f"{d[5:]}: MM中位 {median_v:.1f}{temp_symbol}")
-                    if len(future_forecasts) >= 2:
-                        break
-                if future_forecasts:
-                    msg_lines.append("📅 " + " | ".join(future_forecasts))
-            elif isinstance(mb_daily, list) and len(mb_daily) > 1:
-                # Open-Meteo missing: fallback to Meteoblue daily highs
-                from datetime import datetime, timezone, timedelta
-
-                local_now = datetime.now(timezone.utc).astimezone(
-                    timezone(timedelta(seconds=int(fallback_utc_offset)))
-                )
-                future_forecasts = []
-                for idx in range(1, min(3, len(mb_daily))):
-                    t = _sf(mb_daily[idx])
-                    if t is None:
-                        continue
-                    d = (local_now + timedelta(days=idx)).strftime("%m-%d")
-                    future_forecasts.append(f"{d}: MB {t:.1f}{temp_symbol}")
-                if future_forecasts:
-                    msg_lines.append("📅 " + " | ".join(future_forecasts))
-            elif isinstance(nws_periods, list) and nws_periods:
-                # US fallback: use next daytime NWS periods
-                from datetime import datetime, timezone, timedelta
-
-                local_now = datetime.now(timezone.utc).astimezone(
-                    timezone(timedelta(seconds=int(fallback_utc_offset)))
-                )
-                today_local = local_now.strftime("%Y-%m-%d")
-                future_forecasts = []
-                seen_days = set()
-                for p in nws_periods:
-                    if not p.get("is_daytime"):
-                        continue
-                    temp_v = _sf(p.get("temperature"))
-                    start_time = str(p.get("start_time") or "")
-                    if temp_v is None or "T" not in start_time:
-                        continue
-                    day_str = start_time[:10]
-                    if day_str <= today_local or day_str in seen_days:
-                        continue
-                    seen_days.add(day_str)
-                    future_forecasts.append(f"{day_str[5:]}: NWS {temp_v:.0f}{temp_symbol}")
-                    if len(future_forecasts) >= 2:
-                        break
-                if future_forecasts:
-                    msg_lines.append("📅 " + " | ".join(future_forecasts))
-
-            # --- 3.5 日出日落 + 日照时长 ---
-            sunrises = daily.get("sunrise", [])
-            sunsets = daily.get("sunset", [])
-            sunshine_durations = daily.get("sunshine_duration", [])
-            if sunrises and sunsets:
-                sunrise_t = (
-                    sunrises[0].split("T")[1][:5]
-                    if "T" in str(sunrises[0])
-                    else sunrises[0]
-                )
-                sunset_t = (
-                    sunsets[0].split("T")[1][:5]
-                    if "T" in str(sunsets[0])
-                    else sunsets[0]
-                )
-                sun_line = f"🌅 日出 {sunrise_t} | 🌇 日落 {sunset_t}"
-                if sunshine_durations:
-                    sunshine_hours = sunshine_durations[0] / 3600  # 秒 -> 小时
-                    sun_line += f" | ☀️ 日照 {sunshine_hours:.1f}h"
-                msg_lines.append(sun_line)
-
-            # --- 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
-                else mgm.get("current", {}).get("temp")
-            )
-            max_p = _sf(
-                metar.get("current", {}).get("max_temp_so_far") if metar else None
-            )
-            max_p_time = (
-                metar.get("current", {}).get("max_temp_time") if metar else None
-            )
-            obs_t_str = "N/A"
-            metar_age_min = None  # METAR 数据年龄（分钟）
-            main_source = "METAR" if metar else "MGM"
-
-            if metar:
-                obs_t = metar.get("observation_time", "")
-                try:
-                    if "T" in obs_t:
-                        from datetime import datetime, timezone, timedelta
-
-                        dt = datetime.fromisoformat(obs_t.replace("Z", "+00:00"))
-                        utc_offset = open_meteo.get("utc_offset")
-                        if utc_offset is None:
-                            utc_offset = fallback_utc_offset
-                        local_dt = dt.astimezone(
-                            timezone(timedelta(seconds=int(utc_offset)))
-                        )
-                        obs_t_str = local_dt.strftime("%H:%M")
-                        # 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:
-                        obs_t_str = obs_t.split(" ")[1][:5]
-                    else:
-                        obs_t_str = obs_t
-                except Exception:
-                    obs_t_str = obs_t[:16]
-            elif mgm:
-                m_time = mgm.get("current", {}).get("time", "")
-                if "T" in m_time:
-                    from datetime import datetime, timezone, timedelta
-
-                    dt = datetime.fromisoformat(m_time.replace("Z", "+00:00"))
-                    m_time = dt.astimezone(timezone(timedelta(hours=3))).strftime(
-                        "%H:%M"
-                    )
-                elif " " in m_time:
-                    m_time = m_time.split(" ")[1][:5]
-                obs_t_str = m_time
-
-            # 数据年龄标注
-            age_tag = ""
-            if metar_age_min is not None:
-                if metar_age_min >= 60:
-                    age_tag = f" ⚠️{metar_age_min}分钟前"
-                elif metar_age_min >= 30:
-                    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" (最高: {max_p}{temp_symbol}"
-                if max_p_time:
-                    max_str += f" @{max_p_time}"
-                max_str += f" → WU {settled_val}{temp_symbol})"
-
-            # --- 天气状况总结 ---
-            wx_summary = ""
-            # 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
-
-            if metar_wx:
-                wx_upper = metar_wx.upper().strip()
-                wx_tokens = set(wx_upper.split())
-                rain_codes = {
-                    "RA",
-                    "DZ",
-                    "-RA",
-                    "+RA",
-                    "-DZ",
-                    "+DZ",
-                    "TSRA",
-                    "SHRA",
-                    "FZRA",
-                }
-                snow_codes = {"SN", "GR", "GS", "-SN", "+SN", "BLSN"}
-                fog_codes = {"FG", "BR", "HZ", "FZFG"}
-                ts_codes = {"TS", "TSRA"}
-                if ts_codes & wx_tokens:
-                    wx_summary = "⛈️ 雷暴"
-                elif {"+RA", "+SN"} & wx_tokens:
-                    wx_summary = "🌧️ 大雨" if "+RA" in wx_tokens else "❄️ 大雪"
-                elif rain_codes & wx_tokens:
-                    wx_summary = (
-                        "🌧️ 小雨" if {"-RA", "-DZ", "DZ"} & wx_tokens else "🌧️ 下雨"
-                    )
-                elif snow_codes & wx_tokens:
-                    wx_summary = "❄️ 下雪"
-                elif fog_codes & wx_tokens:
-                    wx_summary = "🌫️ 雾 / 霾"
-
-            # 如果 METAR 没有特殊现象，用云量推断
-            if not wx_summary:
-                # 优先 METAR 云层，回退 MGM
-                cover_code = ""
-                if metar_clouds:
-                    cover_code = metar_clouds[-1].get("cover", "")
-
-                if cover_code in ("SKC", "CLR") or (
-                    cover_code == "" and mgm_cloud is not None and mgm_cloud <= 1
-                ):
-                    wx_summary = "☀️ 晴"
-                elif cover_code == "FEW" or (
-                    cover_code == "" and mgm_cloud is not None and mgm_cloud <= 2
-                ):
-                    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 = "⛅ 晴间多云"
-                elif cover_code == "BKN" or (
-                    cover_code == "" and mgm_cloud is not None and mgm_cloud <= 6
-                ):
-                    wx_summary = "🌥️ 多云"
-                elif cover_code == "OVC" or (
-                    cover_code == "" and mgm_cloud is not None and mgm_cloud <= 8
-                ):
-                    wx_summary = "☁️ 阴天"
-                elif mgm_cloud is not None:
-                    cloud_names = {
-                        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✈️ <b>实测 ({main_source}): {cur_temp}{temp_symbol}</b>{max_str} |{wx_display} | {obs_t_str}{age_tag}"
-            )
-
-            if mgm:
-                m_c = mgm.get("current", {})
-                # 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 = ["北", "东北", "东", "东南", "南", "西南", "西", "西北"]
-                    dir_str = dirs[int((float(wind_dir) + 22.5) % 360 / 45)] + "风"
-
-                # 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"🌡️ 体感: {feels_like}°C")
-                    
-                    # 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 (Bölge/Center): <b>{ankara_center['temp']}°C</b>")
-                        
-                    if humidity is not None:
-                        parts.append(f"💧 {humidity}%")
-                    msg_lines.append(f"   [MGM] {' | '.join(parts)}")
-
-                # 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] 🌬️ {dir_str}{wind_dir}° ({wind_speed_ms} m/s) | 💧 降水: {m_c.get('rain_24h') or 0}mm"
-                    )
-
-                # 新增：气压和云量
-                extra_parts = []
-                pressure = m_c.get("pressure")
-                if pressure is not None:
-                    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: "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"☁️ 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"🌡️ MGM最高: {mgm_max}°C")
-                if extra_parts:
-                    msg_lines.append(f"   [MGM] {' | '.join(extra_parts)}")
-
-            if metar:
-                m_c = metar.get("current", {})
-                wind = m_c.get("wind_speed_kt")
-                wind_dir = m_c.get("wind_dir")
-                vis = m_c.get("visibility_mi")
-                clouds = m_c.get("clouds", [])
-
-                cloud_desc = ""
-                if clouds:
-                    c_map = {
-                        "BKN": "多云",
-                        "OVC": "阴天",
-                        "FEW": "少云",
-                        "SCT": "散云",
-                        "SKC": "晴",
-                        "CLR": "晴",
-                    }
-                    main = clouds[-1]
-                    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} 🌪 {wind or 0}kt ({wind_dir or 0}°) | 👁️ {vis or 10}mi"
-                    )
-
-                if cloud_desc:
-                    msg_lines.append(
-                        f"   {prefix} {cloud_desc} | 👁️ {vis or 10}mi | 🌪 {wind or 0}kt"
-                    )
-
-            # --- 5. 态势特征提取 ---
-            feature_str, ai_context = analyze_weather_trend(
-                weather_data, temp_symbol, city_name
-            )
-            if feature_str:
-                # 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💡 <b>分析</b>:")
-                for line in feature_str.split("\n"):
-                    if line.strip():
-                        msg_lines.append(f"- {line.strip()}")
-
-                # --- 6. Groq AI 深度分析 ---
-                try:
-                    from src.analysis.ai_analyzer import get_ai_analysis
-                    # 构建更全的背景数据给 AI
-
-                    # 补充多模型分歧
-                    mm = weather_data.get("multi_model", {}) or {}
-                    if not isinstance(mm, dict):
-                        mm = {}
-                    if mm.get("forecasts"):
-                        mm_str = " | ".join(
-                            [
-                                f"{k}:{v}{temp_symbol}"
-                                for k, v in mm["forecasts"].items()
-                                if v
-                            ]
-                        )
-                        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"调用 Groq AI 分析失败: {e}")
-
-            msg_lines.append(f"\n💸 本次消耗 <b>{CITY_QUERY_COST}</b> 积分。")
-            bot.send_message(message.chat.id, "\n".join(msg_lines), parse_mode="HTML")
-
         except Exception as e:
             import traceback
 

frontend/.env.example

@@ -1 +1,6 @@
 POLYWEATHER_API_BASE_URL=http://127.0.0.1:8000
+# Optional dashboard guard (Next.js middleware)
+# If set, open dashboard with: /?access_token=<token>
+POLYWEATHER_DASHBOARD_ACCESS_TOKEN=
+# Shared secret forwarded by Next API routes to backend
+POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN=

frontend/app/api/cities/route.ts

@@ -1,4 +1,5 @@
 import { NextResponse } from "next/server";
+import { buildBackendRequestHeaders } from "@/lib/backend-auth";
 
 const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
 
@@ -12,7 +13,7 @@ export async function GET() {
 
   try {
     const res = await fetch(`${API_BASE}/api/cities`, {
-      headers: { Accept: "application/json" },
+      headers: buildBackendRequestHeaders(),
       next: { revalidate: 120 },
     });
     if (!res.ok) {

frontend/app/api/city/[name]/detail/route.ts

@@ -1,4 +1,5 @@
 import { NextRequest, NextResponse } from "next/server";
+import { buildBackendRequestHeaders } from "@/lib/backend-auth";
 
 const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
 
@@ -26,7 +27,7 @@ export async function GET(
 
   try {
     const res = await fetch(url, {
-      headers: { Accept: "application/json" },
+      headers: buildBackendRequestHeaders(),
       cache: "no-store",
     });
     if (!res.ok) {

frontend/app/api/city/[name]/route.ts

@@ -1,4 +1,5 @@
 import { NextRequest, NextResponse } from "next/server";
+import { buildBackendRequestHeaders } from "@/lib/backend-auth";
 
 const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
 
@@ -19,7 +20,7 @@ export async function GET(
 
   try {
     const res = await fetch(url, {
-      headers: { Accept: "application/json" },
+      headers: buildBackendRequestHeaders(),
       cache: "no-store",
     });
     if (!res.ok) {

frontend/app/api/city/[name]/summary/route.ts

@@ -1,4 +1,5 @@
 import { NextRequest, NextResponse } from "next/server";
+import { buildBackendRequestHeaders } from "@/lib/backend-auth";
 
 const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
 
@@ -19,7 +20,7 @@ export async function GET(
 
   try {
     const res = await fetch(url, {
-      headers: { Accept: "application/json" },
+      headers: buildBackendRequestHeaders(),
       cache: "no-store",
     });
     if (!res.ok) {

frontend/app/api/history/[name]/route.ts

@@ -1,4 +1,5 @@
 import { NextResponse } from "next/server";
+import { buildBackendRequestHeaders } from "@/lib/backend-auth";
 
 const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
 
@@ -18,7 +19,7 @@ export async function GET(
 
   try {
     const res = await fetch(url, {
-      headers: { Accept: "application/json" },
+      headers: buildBackendRequestHeaders(),
       cache: "no-store",
     });
     if (!res.ok) {

frontend/app/entitlement-required/page.tsx

@@ -0,0 +1,46 @@
+type Props = {
+  searchParams?: Promise<{ next?: string }>;
+};
+
+export default async function EntitlementRequiredPage({ searchParams }: Props) {
+  const params = (await searchParams) || {};
+  const nextPath = params.next || "/";
+
+  return (
+    <main
+      style={{
+        minHeight: "100vh",
+        display: "grid",
+        placeItems: "center",
+        background:
+          "radial-gradient(circle at 20% 20%, #13264f 0%, #071127 45%, #040812 100%)",
+        color: "#d6e2ff",
+        padding: "24px",
+      }}
+    >
+      <section
+        style={{
+          width: "100%",
+          maxWidth: 720,
+          border: "1px solid rgba(68, 92, 140, 0.45)",
+          borderRadius: 16,
+          padding: 24,
+          background: "rgba(9, 18, 36, 0.88)",
+          boxShadow: "0 20px 50px rgba(0, 0, 0, 0.35)",
+        }}
+      >
+        <h1 style={{ margin: 0, fontSize: 28, lineHeight: 1.2 }}>
+          Entitlement Required
+        </h1>
+        <p style={{ marginTop: 12, color: "#9fb2da", lineHeight: 1.6 }}>
+          This dashboard is protected. Append{" "}
+          <code>?access_token=&lt;your-token&gt;</code> to the URL once, and
+          the session cookie will be set automatically.
+        </p>
+        <p style={{ marginTop: 12, color: "#9fb2da", lineHeight: 1.6 }}>
+          Requested path: <code>{nextPath}</code>
+        </p>
+      </section>
+    </main>
+  );
+}

frontend/lib/backend-auth.ts

@@ -0,0 +1,14 @@
+export const BACKEND_ENTITLEMENT_HEADER = "x-polyweather-entitlement";
+
+export function buildBackendRequestHeaders(): HeadersInit {
+  const headers: HeadersInit = {
+    Accept: "application/json",
+  };
+
+  const token = process.env.POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN?.trim();
+  if (token) {
+    headers[BACKEND_ENTITLEMENT_HEADER] = token;
+  }
+
+  return headers;
+}

frontend/middleware.ts

@@ -0,0 +1,69 @@
+import { NextRequest, NextResponse } from "next/server";
+
+const SESSION_COOKIE = "polyweather_entitlement";
+
+function isStaticAsset(pathname: string) {
+  return (
+    pathname.startsWith("/_next/") ||
+    pathname.startsWith("/favicon") ||
+    pathname.startsWith("/robots.txt") ||
+    pathname.startsWith("/sitemap.xml") ||
+    pathname.startsWith("/icons/") ||
+    pathname.startsWith("/images/") ||
+    pathname.startsWith("/static/")
+  );
+}
+
+function isPublicPage(pathname: string) {
+  return pathname === "/entitlement-required";
+}
+
+export function middleware(request: NextRequest) {
+  const requiredToken = process.env.POLYWEATHER_DASHBOARD_ACCESS_TOKEN?.trim();
+  if (!requiredToken) {
+    return NextResponse.next();
+  }
+
+  const { pathname, searchParams } = request.nextUrl;
+  if (isStaticAsset(pathname) || isPublicPage(pathname)) {
+    return NextResponse.next();
+  }
+
+  const cookieToken = request.cookies.get(SESSION_COOKIE)?.value;
+  if (cookieToken && cookieToken === requiredToken) {
+    return NextResponse.next();
+  }
+
+  const queryToken = searchParams.get("access_token");
+  if (queryToken && queryToken === requiredToken) {
+    const cleanUrl = request.nextUrl.clone();
+    cleanUrl.searchParams.delete("access_token");
+
+    const response = NextResponse.redirect(cleanUrl);
+    response.cookies.set(SESSION_COOKIE, requiredToken, {
+      httpOnly: true,
+      sameSite: "lax",
+      secure: cleanUrl.protocol === "https:",
+      path: "/",
+      maxAge: 60 * 60 * 12,
+    });
+    return response;
+  }
+
+  if (pathname.startsWith("/api/")) {
+    return NextResponse.json(
+      { error: "Unauthorized", detail: "Entitlement token required" },
+      { status: 401 },
+    );
+  }
+
+  const deniedUrl = request.nextUrl.clone();
+  deniedUrl.pathname = "/entitlement-required";
+  deniedUrl.search = "";
+  deniedUrl.searchParams.set("next", pathname);
+  return NextResponse.redirect(deniedUrl);
+}
+
+export const config = {
+  matcher: ["/((?!_next/static|_next/image).*)"],
+};

src/analysis/city_query_service.py

@@ -0,0 +1,468 @@
+from __future__ import annotations
+
+from datetime import datetime, timezone, timedelta
+from typing import Any, Dict, List, Optional, Tuple
+
+from loguru import logger
+
+from src.analysis.trend_engine import analyze_weather_trend
+from src.data_collection.city_registry import ALIASES, CITY_REGISTRY
+from src.data_collection.city_risk_profiles import get_city_risk_profile
+
+
+FAHRENHEIT_CITIES = {
+    "dallas",
+    "new york",
+    "chicago",
+    "miami",
+    "atlanta",
+    "seattle",
+}
+
+
+def _sf(value: Any) -> Optional[float]:
+    if value is None:
+        return None
+    try:
+        return float(value)
+    except Exception:
+        return None
+
+
+def resolve_city_name(city_input: str) -> Tuple[Optional[str], List[str]]:
+    city_input_norm = city_input.strip().lower()
+    supported = list(CITY_REGISTRY.keys())
+
+    # 1) Exact alias/name
+    city_name = ALIASES.get(city_input_norm)
+    if not city_name and city_input_norm in supported:
+        city_name = city_input_norm
+
+    # 2) Prefix match
+    if not city_name and len(city_input_norm) >= 2:
+        for alias, canonical in ALIASES.items():
+            if alias.startswith(city_input_norm):
+                city_name = canonical
+                break
+        if not city_name:
+            for canonical in supported:
+                if canonical.startswith(city_input_norm):
+                    city_name = canonical
+                    break
+
+    return city_name, sorted(supported)
+
+
+def _render_local_time(
+    open_meteo: Dict[str, Any],
+    metar: Dict[str, Any],
+    fallback_utc_offset: int,
+) -> str:
+    local_time = (open_meteo.get("current") or {}).get("local_time", "")
+    if " " in str(local_time):
+        return str(local_time).split(" ")[1][:5]
+
+    metar_obs = metar.get("observation_time", "") if metar else ""
+    if "T" in str(metar_obs):
+        try:
+            dt = datetime.fromisoformat(str(metar_obs).replace("Z", "+00:00"))
+            utc_offset = open_meteo.get("utc_offset")
+            if utc_offset is None:
+                utc_offset = fallback_utc_offset
+            local_dt = dt.astimezone(timezone(timedelta(seconds=int(utc_offset))))
+            return local_dt.strftime("%H:%M")
+        except Exception:
+            return str(metar_obs).split("T")[1][:5]
+
+    if " " in str(metar_obs):
+        return str(metar_obs).split(" ")[1][:5]
+    if metar_obs:
+        return str(metar_obs)[:5]
+
+    try:
+        local_now = datetime.now(timezone.utc).astimezone(
+            timezone(timedelta(seconds=int(fallback_utc_offset)))
+        )
+        return local_now.strftime("%H:%M")
+    except Exception:
+        return "N/A"
+
+
+def _append_future_forecast_lines(
+    lines: List[str],
+    weather_data: Dict[str, Any],
+    dates: List[str],
+    max_temps: List[Any],
+    temp_symbol: str,
+    fallback_utc_offset: int,
+) -> None:
+    mgm = weather_data.get("mgm") or {}
+    mgm_daily = (mgm.get("daily_forecasts") or {}) if isinstance(mgm, dict) else {}
+    mm_raw = weather_data.get("multi_model") or {}
+    mm_daily = mm_raw.get("daily_forecasts", {}) if isinstance(mm_raw, dict) else {}
+    mb_daily = (weather_data.get("meteoblue") or {}).get("daily_highs", []) or []
+    nws_periods = (weather_data.get("nws") or {}).get("forecast_periods", []) or []
+
+    if len(dates) > 1:
+        future_forecasts = []
+        for d, t in zip(dates[1:], max_temps[1:]):
+            mgm_value = mgm_daily.get(d) if isinstance(mgm_daily, dict) else None
+            if mgm_value is not None:
+                future_forecasts.append(
+                    f"{d[5:]}: {t}{temp_symbol} | 🇺🇸 <b>MGM: {mgm_value}{temp_symbol}</b>"
+                )
+            else:
+                future_forecasts.append(f"{d[5:]}: {t}{temp_symbol}")
+        lines.append("📅 " + " | ".join(future_forecasts))
+        return
+
+    local_now = datetime.now(timezone.utc).astimezone(
+        timezone(timedelta(seconds=int(fallback_utc_offset)))
+    )
+    today_local = local_now.strftime("%Y-%m-%d")
+
+    if isinstance(mgm_daily, dict) and mgm_daily:
+        future = []
+        for day in sorted(mgm_daily.keys()):
+            if day <= today_local:
+                continue
+            day_temp = mgm_daily.get(day)
+            if day_temp is None:
+                continue
+            future.append(f"{day[5:]}: {day_temp}{temp_symbol}")
+            if len(future) >= 2:
+                break
+        if future:
+            lines.append("📅 " + " | ".join(future))
+        return
+
+    if isinstance(mm_daily, dict) and mm_daily:
+        future = []
+        for day in sorted(mm_daily.keys()):
+            if day <= today_local:
+                continue
+            models = mm_daily.get(day, {}) or {}
+            vals = [_sf(v) for v in models.values()]
+            vals = [v for v in vals if v is not None]
+            if not vals:
+                continue
+            vals.sort()
+            median = vals[len(vals) // 2]
+            future.append(f"{day[5:]}: MM中位 {median:.1f}{temp_symbol}")
+            if len(future) >= 2:
+                break
+        if future:
+            lines.append("📅 " + " | ".join(future))
+        return
+
+    if isinstance(mb_daily, list) and len(mb_daily) > 1:
+        future = []
+        for idx in range(1, min(3, len(mb_daily))):
+            day_temp = _sf(mb_daily[idx])
+            if day_temp is None:
+                continue
+            day = (local_now + timedelta(days=idx)).strftime("%m-%d")
+            future.append(f"{day}: MB {day_temp:.1f}{temp_symbol}")
+        if future:
+            lines.append("📅 " + " | ".join(future))
+        return
+
+    if isinstance(nws_periods, list) and nws_periods:
+        future = []
+        seen_days = set()
+        for period in nws_periods:
+            if not period.get("is_daytime"):
+                continue
+            day_temp = _sf(period.get("temperature"))
+            start_time = str(period.get("start_time") or "")
+            if day_temp is None or "T" not in start_time:
+                continue
+            day = start_time[:10]
+            if day <= today_local or day in seen_days:
+                continue
+            seen_days.add(day)
+            future.append(f"{day[5:]}: NWS {day_temp:.0f}{temp_symbol}")
+            if len(future) >= 2:
+                break
+        if future:
+            lines.append("📅 " + " | ".join(future))
+
+
+def _build_wx_summary(
+    metar_current: Dict[str, Any],
+    metar_clouds: List[Dict[str, Any]],
+    mgm_cloud: Optional[Any],
+) -> str:
+    wx_desc = str(metar_current.get("wx_desc") or "").upper().strip()
+    if wx_desc:
+        tokens = set(wx_desc.split())
+        rain_codes = {"RA", "DZ", "-RA", "+RA", "-DZ", "+DZ", "TSRA", "SHRA", "FZRA"}
+        snow_codes = {"SN", "GR", "GS", "-SN", "+SN", "BLSN"}
+        fog_codes = {"FG", "BR", "HZ", "FZFG"}
+        ts_codes = {"TS", "TSRA"}
+        if ts_codes & tokens:
+            return "⛈️ 雷暴"
+        if {"+RA", "+SN"} & tokens:
+            return "🌧️ 大雨" if "+RA" in tokens else "❄️ 大雪"
+        if rain_codes & tokens:
+            return "🌧️ 小雨" if {"-RA", "-DZ", "DZ"} & tokens else "🌧️ 下雨"
+        if snow_codes & tokens:
+            return "❄️ 下雪"
+        if fog_codes & tokens:
+            return "🌫️ 雾 / 霾"
+
+    cover_code = ""
+    if metar_clouds:
+        cover_code = str((metar_clouds[-1] or {}).get("cover") or "")
+
+    if cover_code in ("SKC", "CLR") or (cover_code == "" and mgm_cloud is not None and mgm_cloud <= 1):
+        return "☀️ 晴"
+    if cover_code == "FEW" or (cover_code == "" and mgm_cloud is not None and mgm_cloud <= 2):
+        return "🌤️ 晴间少云"
+    if cover_code == "SCT" or (cover_code == "" and mgm_cloud is not None and mgm_cloud <= 4):
+        return "⛅ 晴间多云"
+    if cover_code == "BKN" or (cover_code == "" and mgm_cloud is not None and mgm_cloud <= 6):
+        return "🌥️ 多云"
+    if cover_code == "OVC" or (cover_code == "" and mgm_cloud is not None and mgm_cloud <= 8):
+        return "☁️ 阴天"
+    if mgm_cloud is not None:
+        cloud_names = {
+            0: "☀️ 晴",
+            1: "☀️ 晴",
+            2: "🌤️ 少云",
+            3: "⛅ 散云",
+            4: "⛅ 散云",
+            5: "🌥️ 多云",
+            6: "🌥️ 多云",
+            7: "☁️ 阴",
+            8: "☁️ 阴天",
+        }
+        return cloud_names.get(int(mgm_cloud), "")
+    return ""
+
+
+def build_city_query_report(
+    city_name: str,
+    weather_data: Dict[str, Any],
+    city_query_cost: int,
+) -> str:
+    open_meteo = weather_data.get("open-meteo", {}) or {}
+    metar = weather_data.get("metar", {}) or {}
+    mgm = weather_data.get("mgm") or {}
+    city_meta = CITY_REGISTRY.get(city_name.lower(), {})
+    fallback_utc_offset = int(city_meta.get("tz_offset", 0))
+    nws_periods = ((weather_data.get("nws") or {}).get("forecast_periods") or [])
+    if nws_periods:
+        try:
+            first_start = nws_periods[0].get("start_time")
+            if first_start:
+                maybe_dt = datetime.fromisoformat(str(first_start))
+                if maybe_dt.utcoffset() is not None:
+                    fallback_utc_offset = int(maybe_dt.utcoffset().total_seconds())
+        except Exception:
+            pass
+
+    city_is_fahrenheit = city_name.strip().lower() in FAHRENHEIT_CITIES
+    temp_symbol = "°F" if city_is_fahrenheit else "°C"
+
+    time_str = _render_local_time(open_meteo, metar, fallback_utc_offset)
+    risk_profile = get_city_risk_profile(city_name)
+    risk_emoji = risk_profile.get("risk_level", "⚠️") if risk_profile else "⚠️"
+
+    msg_lines = [f"📍 <b>{city_name.title()}</b> ({time_str}) {risk_emoji}"]
+    if risk_profile:
+        bias = risk_profile.get("bias", "±0.0")
+        msg_lines.append(
+            f"⚠️ {risk_profile.get('airport_name', '')}: {bias}{temp_symbol} | {risk_profile.get('warning', '')}"
+        )
+
+    daily = open_meteo.get("daily", {}) or {}
+    dates = (daily.get("time") or [])[:3]
+    max_temps = (daily.get("temperature_2m_max") or [])[:3]
+
+    nws_high = _sf((weather_data.get("nws") or {}).get("today_high"))
+    mgm_high = _sf((mgm.get("today_high") if isinstance(mgm, dict) else None))
+    mb_high = _sf((weather_data.get("meteoblue") or {}).get("today_high"))
+    metar_max_so_far = _sf((metar.get("current") or {}).get("max_temp_so_far"))
+
+    today_t = _sf(max_temps[0]) if max_temps else None
+    fallback_source = None
+    metar_only_fallback = False
+    if today_t is None:
+        for source_name, candidate in (("MB", mb_high), ("NWS", nws_high), ("MGM", mgm_high)):
+            if candidate is not None:
+                today_t = candidate
+                fallback_source = source_name
+                break
+    if today_t is None and metar_max_so_far is not None:
+        today_t = metar_max_so_far
+        metar_only_fallback = True
+
+    today_t_display = f"{today_t:.1f}" if isinstance(today_t, (int, float)) else "N/A"
+    sources = ["Open-Meteo"] if max_temps else []
+    comp_parts: List[str] = []
+
+    if mb_high is not None:
+        if "MB" not in sources:
+            sources.append("MB")
+        if fallback_source != "MB":
+            comp_parts.append(f"MB: {mb_high:.1f}{temp_symbol}")
+    if nws_high is not None:
+        if "NWS" not in sources:
+            sources.append("NWS")
+        if fallback_source != "NWS":
+            comp_parts.append(f"NWS: {nws_high:.1f}{temp_symbol}")
+    if mgm_high is not None:
+        if "MGM" not in sources:
+            sources.append("MGM")
+        if fallback_source != "MGM":
+            comp_parts.append(f"MGM: {mgm_high:.1f}{temp_symbol}")
+    if fallback_source and fallback_source not in sources:
+        sources.append(fallback_source)
+    if metar_only_fallback:
+        if not sources:
+            sources = ["Model unavailable"]
+        comp_parts.append(f"METAR实测回退: {metar_max_so_far:.1f}{temp_symbol}")
+    if not sources:
+        sources = ["N/A"]
+
+    divergence_warning = ""
+    base_for_divergence = _sf(max_temps[0]) if max_temps else today_t
+    if mb_high is not None and base_for_divergence is not None:
+        diff = abs(mb_high - base_for_divergence)
+        threshold = 5.0 if city_is_fahrenheit else 2.5
+        if diff > threshold:
+            divergence_warning = f" ⚠️ <b>模型显著分歧 ({diff:.1f}{temp_symbol})</b>"
+
+    comp_str = f" ({' | '.join(comp_parts)})" if comp_parts else ""
+    msg_lines.append(f"\n📊 <b>预报 ({' | '.join(sources)})</b>")
+    msg_lines.append(
+        f"👉 <b>今天: {today_t_display}{temp_symbol}{comp_str}</b>{divergence_warning}"
+    )
+
+    _append_future_forecast_lines(
+        lines=msg_lines,
+        weather_data=weather_data,
+        dates=dates,
+        max_temps=max_temps,
+        temp_symbol=temp_symbol,
+        fallback_utc_offset=fallback_utc_offset,
+    )
+
+    sunrises = daily.get("sunrise", []) or []
+    sunsets = daily.get("sunset", []) or []
+    sunshine_durations = daily.get("sunshine_duration", []) or []
+    if sunrises and sunsets:
+        sunrise_t = str(sunrises[0]).split("T")[1][:5] if "T" in str(sunrises[0]) else str(sunrises[0])
+        sunset_t = str(sunsets[0]).split("T")[1][:5] if "T" in str(sunsets[0]) else str(sunsets[0])
+        sun_line = f"🌅 日出 {sunrise_t} | 🌇 日落 {sunset_t}"
+        if sunshine_durations:
+            sun_line += f" | ☀️ 日照 {float(sunshine_durations[0]) / 3600:.1f}h"
+        msg_lines.append(sun_line)
+
+    metar_current = metar.get("current", {}) if isinstance(metar, dict) else {}
+    mgm_current = mgm.get("current", {}) if isinstance(mgm, dict) else {}
+    cur_temp = _sf(metar_current.get("temp"))
+    if cur_temp is None:
+        cur_temp = _sf(mgm_current.get("temp"))
+    max_p = _sf(metar_current.get("max_temp_so_far"))
+    max_p_time = metar_current.get("max_temp_time")
+    obs_t_str = "N/A"
+    metar_age_min = None
+    main_source = "METAR" if metar else "MGM"
+
+    if metar and metar.get("observation_time"):
+        obs_t = str(metar.get("observation_time"))
+        try:
+            if "T" in obs_t:
+                dt = datetime.fromisoformat(obs_t.replace("Z", "+00:00"))
+                utc_offset = open_meteo.get("utc_offset")
+                if utc_offset is None:
+                    utc_offset = fallback_utc_offset
+                local_dt = dt.astimezone(timezone(timedelta(seconds=int(utc_offset))))
+                obs_t_str = local_dt.strftime("%H:%M")
+                metar_age_min = int((datetime.now(timezone.utc) - dt).total_seconds() / 60)
+            elif " " in obs_t:
+                obs_t_str = obs_t.split(" ")[1][:5]
+            else:
+                obs_t_str = obs_t
+        except Exception:
+            obs_t_str = obs_t[:16]
+    elif mgm:
+        mgm_time = str(mgm_current.get("time") or "")
+        if "T" in mgm_time:
+            dt = datetime.fromisoformat(mgm_time.replace("Z", "+00:00"))
+            mgm_time = dt.astimezone(timezone(timedelta(hours=3))).strftime("%H:%M")
+        elif " " in mgm_time:
+            mgm_time = mgm_time.split(" ")[1][:5]
+        obs_t_str = mgm_time or "N/A"
+
+    age_tag = ""
+    if metar_age_min is not None:
+        if metar_age_min >= 60:
+            age_tag = f" ⚠️{metar_age_min}分钟前"
+        elif metar_age_min >= 30:
+            age_tag = f" 🔔{metar_age_min}分钟前"
+
+    max_str = ""
+    if max_p is not None:
+        settled_val = int(max_p + 0.5)
+        max_str = f" (最高: {max_p}{temp_symbol}"
+        if max_p_time:
+            max_str += f" @{max_p_time}"
+        max_str += f" → WU {settled_val}{temp_symbol})"
+
+    metar_clouds = metar_current.get("clouds", []) if isinstance(metar_current, dict) else []
+    mgm_cloud = mgm_current.get("cloud_cover") if isinstance(mgm_current, dict) else None
+    wx_summary = _build_wx_summary(metar_current, metar_clouds, mgm_cloud)
+    wx_display = f" {wx_summary}" if wx_summary else ""
+    msg_lines.append(
+        f"\n✈️ <b>实测 ({main_source}): {cur_temp}{temp_symbol}</b>{max_str} |{wx_display} | {obs_t_str}{age_tag}"
+    )
+
+    if metar:
+        wind = metar_current.get("wind_speed_kt")
+        wind_dir = metar_current.get("wind_dir")
+        vis = metar_current.get("visibility_mi")
+        if not mgm:
+            msg_lines.append(f"   [METAR] 🌪 {wind or 0}kt ({wind_dir or 0}°) | 👁️ {vis or 10}mi")
+    if mgm:
+        wind_dir = mgm_current.get("wind_dir")
+        wind_speed_ms = mgm_current.get("wind_speed_ms")
+        if wind_dir is not None and wind_speed_ms is not None:
+            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"
+            msg_lines.append(
+                f"   [MGM] 🌬️ {dir_str}{wind_dir}° ({wind_speed_ms} m/s) | 💧 降水: {mgm_current.get('rain_24h') or 0}mm"
+            )
+
+    feature_str, ai_context, _structured = analyze_weather_trend(weather_data, temp_symbol, city_name)
+    if feature_str:
+        msg_lines.append("\n💡 <b>分析</b>:")
+        for line in feature_str.split("\n"):
+            if line.strip():
+                msg_lines.append(f"- {line.strip()}")
+
+        try:
+            from src.analysis.ai_analyzer import get_ai_analysis
+
+            mm = weather_data.get("multi_model", {}) or {}
+            if not isinstance(mm, dict):
+                mm = {}
+            if mm.get("forecasts"):
+                mm_parts = [
+                    f"{k}:{v}{temp_symbol}"
+                    for k, v in (mm.get("forecasts") or {}).items()
+                    if v is not None
+                ]
+                if mm_parts:
+                    ai_context += f"\n模型分歧: {' | '.join(mm_parts)}"
+
+            ai_result = get_ai_analysis(ai_context, city_name, temp_symbol)
+            if ai_result:
+                msg_lines.append(f"\n{ai_result}")
+        except Exception as exc:
+            logger.error(f"调用 Groq AI 分析失败: {exc}")
+
+    msg_lines.append(f"\n💸 本次消耗 <b>{city_query_cost}</b> 积分。")
+    return "\n".join(msg_lines)

src/analysis/market_alert_engine.py

@@ -1013,6 +1013,154 @@ def _build_telegram_messages_mispricing(
     return {"zh": "\n".join(lines_zh), "en": "\n".join(lines_en)}
 
 
+def _select_rule_evidence(rule: Dict[str, Any], keys: List[str]) -> Dict[str, Any]:
+    out: Dict[str, Any] = {}
+    for key in keys:
+        if key in rule:
+            out[key] = rule.get(key)
+    return out
+
+
+def _build_alert_evidence(
+    city_weather: Dict[str, Any],
+    rules: Dict[str, Dict[str, Any]],
+    triggered: List[Dict[str, Any]],
+    suppression: Dict[str, Any],
+    market_snapshot: Dict[str, Any],
+    temp_symbol: str,
+) -> Dict[str, Any]:
+    current = city_weather.get("current") or {}
+    deb = city_weather.get("deb") or {}
+
+    momentum = rules.get("momentum_spike") or {}
+    breakthrough = rules.get("forecast_breakthrough") or {}
+    advection = rules.get("advection") or {}
+    ankara_center = rules.get("ankara_center_deb_hit") or {}
+
+    top_rows = []
+    for row in (market_snapshot.get("top_bucket_rows") or [])[:4]:
+        if not isinstance(row, dict):
+            continue
+        top_rows.append(
+            {
+                "label": row.get("label"),
+                "probability": row.get("probability"),
+                "yes_buy": row.get("yes_buy"),
+                "yes_sell": row.get("yes_sell"),
+                "market_url": row.get("market_url"),
+            }
+        )
+
+    trigger_types = [row.get("type") for row in triggered if row.get("type")]
+    forecast_bucket = market_snapshot.get("forecast_bucket") or {}
+
+    return {
+        "version": 1,
+        "city": city_weather.get("name"),
+        "generated_local_time": city_weather.get("local_time"),
+        "observed_at": current.get("obs_time"),
+        "temp_symbol": temp_symbol,
+        "inputs": {
+            "current_temp": _sf(current.get("temp")),
+            "deb_prediction": _sf(deb.get("prediction")),
+            "wu_settle": current.get("wu_settle"),
+            "obs_age_min": current.get("obs_age_min"),
+        },
+        "trigger_summary": {
+            "trigger_count": len(trigger_types),
+            "trigger_types": trigger_types,
+            "suppressed": bool(suppression.get("suppressed")),
+            "suppression_reason": suppression.get("reason"),
+            "suppression_snapshot": _select_rule_evidence(
+                suppression,
+                [
+                    "minutes_since_peak",
+                    "rollback",
+                    "rollback_threshold",
+                    "max_temp_time",
+                    "max_so_far",
+                    "current_temp",
+                ],
+            ),
+        },
+        "rules": {
+            "momentum_spike": _select_rule_evidence(
+                momentum,
+                [
+                    "triggered",
+                    "direction",
+                    "delta_temp",
+                    "delta_minutes",
+                    "slope_30m",
+                    "threshold_30m",
+                ],
+            ),
+            "forecast_breakthrough": _select_rule_evidence(
+                breakthrough,
+                [
+                    "triggered",
+                    "baseline_model",
+                    "baseline_high",
+                    "current_temp",
+                    "margin",
+                    "threshold",
+                    "model_coverage",
+                ],
+            ),
+            "advection": _select_rule_evidence(
+                advection,
+                [
+                    "triggered",
+                    "lead_delta",
+                    "threshold_delta",
+                    "wind_now",
+                    "wind_prev",
+                    "turned_southerly",
+                    "wind_alignment_deg",
+                    "lead_window_minutes",
+                ],
+            ),
+            "ankara_center_deb_hit": _select_rule_evidence(
+                ankara_center,
+                [
+                    "triggered",
+                    "deb_prediction",
+                    "airport_temp",
+                    "margin_vs_deb",
+                    "center_lead_vs_airport",
+                ],
+            ),
+        },
+        "market": {
+            "available": bool(market_snapshot.get("available")),
+            "market_prob": market_snapshot.get("market_prob"),
+            "model_prob": market_snapshot.get("model_prob"),
+            "edge_percent": market_snapshot.get("edge_percent"),
+            "yes_buy": market_snapshot.get("yes_buy"),
+            "yes_sell": market_snapshot.get("yes_sell"),
+            "spread": market_snapshot.get("spread"),
+            "signal_label": market_snapshot.get("signal_label"),
+            "confidence": market_snapshot.get("confidence"),
+            "top_bucket": market_snapshot.get("top_bucket"),
+            "top_bucket_prob": market_snapshot.get("top_bucket_prob"),
+            "open_meteo_today_high_c": market_snapshot.get("open_meteo_today_high_c"),
+            "open_meteo_settlement": market_snapshot.get("open_meteo_settlement"),
+            "forecast_bucket": {
+                "label": forecast_bucket.get("label"),
+                "probability": forecast_bucket.get("probability"),
+                "yes_buy": forecast_bucket.get("yes_buy"),
+                "yes_sell": forecast_bucket.get("yes_sell"),
+                "market_url": forecast_bucket.get("market_url"),
+            }
+            if isinstance(forecast_bucket, dict)
+            else None,
+            "top4": top_rows,
+            "market_url": market_snapshot.get("market_url"),
+            "primary_market_url": market_snapshot.get("primary_market_url"),
+        },
+    }
+
+
 def build_trading_alerts(
     city_weather: Dict[str, Any],
     map_url: Optional[str] = None,
@@ -1065,6 +1213,14 @@ def build_trading_alerts(
         rules=rules,
         market_snapshot=market_snapshot,
     )
+    evidence = _build_alert_evidence(
+        city_weather=city_weather,
+        rules=rules,
+        triggered=triggered,
+        suppression=suppression,
+        market_snapshot=market_snapshot,
+        temp_symbol=temp_symbol,
+    )
 
     return {
         "city": city,
@@ -1076,6 +1232,7 @@ def build_trading_alerts(
         "market_snapshot": market_snapshot,
         "suppression": suppression,
         "triggered_alerts": triggered,
+        "evidence": evidence,
         "telegram": telegram,
     }
 

src/utils/telegram_push.py

@@ -187,6 +187,53 @@ def _trigger_type_key(alert_payload: Dict[str, Any]) -> str:
     return "|".join(trigger_types)
 
 
+def _evidence_brief(alert_payload: Dict[str, Any]) -> str:
+    evidence = alert_payload.get("evidence") or {}
+    if not isinstance(evidence, dict):
+        return "--"
+
+    trigger_summary = evidence.get("trigger_summary") or {}
+    rules = evidence.get("rules") or {}
+    market = evidence.get("market") or {}
+    momentum = rules.get("momentum_spike") or {}
+    advection = rules.get("advection") or {}
+    breakthrough = rules.get("forecast_breakthrough") or {}
+
+    parts: List[str] = []
+    trigger_types = trigger_summary.get("trigger_types")
+    if isinstance(trigger_types, list) and trigger_types:
+        parts.append(f"triggers={','.join(str(t) for t in trigger_types)}")
+
+    slope = momentum.get("slope_30m")
+    if slope is not None:
+        parts.append(f"slope_30m={slope}")
+
+    lead_delta = advection.get("lead_delta")
+    if lead_delta is not None:
+        parts.append(f"lead_delta={lead_delta}")
+
+    margin = breakthrough.get("margin")
+    if margin is not None:
+        parts.append(f"break_margin={margin}")
+
+    edge = market.get("edge_percent")
+    if edge is not None:
+        parts.append(f"edge_pct={edge}")
+
+    forecast_bucket = market.get("forecast_bucket") or {}
+    if isinstance(forecast_bucket, dict):
+        label = str(forecast_bucket.get("label") or "").strip()
+        yes_buy = forecast_bucket.get("yes_buy")
+        if label:
+            parts.append(f"bucket={label}")
+        if yes_buy is not None:
+            parts.append(f"yes_buy={yes_buy}")
+
+    if not parts:
+        return "--"
+    return "; ".join(parts)
+
+
 def _alert_signature(alert_payload: Dict[str, Any]) -> str:
     rules = alert_payload.get("rules") or {}
     center_deb = rules.get("ankara_center_deb_hit") or {}
@@ -321,11 +368,13 @@ def _maybe_send_alert(
         "severity": alert_payload.get("severity"),
         "ts": now_ts,
         "active": True,
+        "evidence": alert_payload.get("evidence"),
     }
     state.setdefault("by_signature", {})[signature] = now_ts
     logger.info(
         f"trade alert pushed city={city} severity={alert_payload.get('severity')} "
-        f"trigger_count={alert_payload.get('trigger_count')} trigger_key={trigger_key}"
+        f"trigger_count={alert_payload.get('trigger_count')} trigger_key={trigger_key} "
+        f"evidence={_evidence_brief(alert_payload)}"
     )
     return True
 
@@ -340,7 +389,13 @@ def start_trade_alert_push_loop(bot: Any, config: Dict[str, Any]) -> Optional[th
         logger.warning("telegram alert push loop skipped: TELEGRAM_CHAT_ID is not set")
         return None
 
-    interval_sec = max(60, _env_int("TELEGRAM_ALERT_PUSH_INTERVAL_SEC", 300))
+    mispricing_only = _env_bool("TELEGRAM_ALERT_MISPRICING_ONLY", True)
+    if mispricing_only:
+        interval_sec = max(
+            300, _env_int("TELEGRAM_ALERT_MISPRICING_INTERVAL_SEC", 7200)
+        )
+    else:
+        interval_sec = max(60, _env_int("TELEGRAM_ALERT_PUSH_INTERVAL_SEC", 300))
     cooldown_sec = max(interval_sec, _env_int("TELEGRAM_ALERT_PUSH_COOLDOWN_SEC", 1800))
     min_trigger_count = max(1, _env_int("TELEGRAM_ALERT_MIN_TRIGGER_COUNT", 2))
     min_severity = os.getenv("TELEGRAM_ALERT_MIN_SEVERITY", "medium").strip().lower()
@@ -353,7 +408,8 @@ def start_trade_alert_push_loop(bot: Any, config: Dict[str, Any]) -> Optional[th
         except Exception:
             logger.exception(f"failed to initialize telegram push state path={state_path}")
         logger.info(
-            f"telegram alert push loop started cities={len(cities)} interval={interval_sec}s "
+            f"telegram alert push loop started mode={'mispricing-only' if mispricing_only else 'full'} "
+            f"cities={len(cities)} interval={interval_sec}s "
             f"cooldown={cooldown_sec}s min_triggers={min_trigger_count} min_severity={min_severity} "
             f"state_path={state_path}"
         )

web/app.py

@@ -21,7 +21,7 @@ if _root not in sys.path:
 if _file_dir not in sys.path:
     sys.path.insert(0, _file_dir)
 
-from fastapi import FastAPI, HTTPException
+from fastapi import FastAPI, HTTPException, Request
 from fastapi.middleware.cors import CORSMiddleware
 from loguru import logger
 
@@ -77,6 +77,45 @@ CACHE_TTL = 300
 CACHE_TTL_ANKARA = 60  # Ankara measurement updates frequent, narrower cache
 
 
+def _env_bool(name: str, default: bool = False) -> bool:
+    raw = os.getenv(name)
+    if raw is None:
+        return default
+    return raw.strip().lower() in {"1", "true", "yes", "on"}
+
+
+_ENTITLEMENT_GUARD_ENABLED = _env_bool("POLYWEATHER_REQUIRE_ENTITLEMENT", False)
+_ENTITLEMENT_HEADER = "x-polyweather-entitlement"
+_ENTITLEMENT_TOKEN = (os.getenv("POLYWEATHER_BACKEND_ENTITLEMENT_TOKEN") or "").strip()
+
+
+def _extract_bearer_token(auth_header: Optional[str]) -> Optional[str]:
+    if not auth_header:
+        return None
+    parts = auth_header.strip().split()
+    if len(parts) == 2 and parts[0].lower() == "bearer":
+        return parts[1].strip()
+    return None
+
+
+def _assert_entitlement(request: Request) -> None:
+    if not _ENTITLEMENT_GUARD_ENABLED:
+        return
+
+    if not _ENTITLEMENT_TOKEN:
+        raise HTTPException(
+            status_code=503,
+            detail="Entitlement guard is enabled but backend token is not configured",
+        )
+
+    token = request.headers.get(_ENTITLEMENT_HEADER)
+    if not token:
+        token = _extract_bearer_token(request.headers.get("authorization"))
+
+    if token != _ENTITLEMENT_TOKEN:
+        raise HTTPException(status_code=401, detail="Unauthorized")
+
+
 def _sf(v) -> Optional[float]:
     """Safe float conversion."""
     if v is None:
@@ -672,8 +711,9 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
 #  Routes
 # ──────────────────────────────────────────────────────────
 @app.get("/api/cities")
-async def list_cities():
+async def list_cities(request: Request):
     """Return all supported cities with coordinates and risk level."""
+    _assert_entitlement(request)
     try:
         out = []
         for name, info in CITIES.items():
@@ -701,8 +741,9 @@ async def list_cities():
 
 
 @app.get("/api/city/{name}")
-async def city_detail(name: str, force_refresh: bool = False):
+async def city_detail(request: Request, name: str, force_refresh: bool = False):
     """Return full weather analysis for a single city."""
+    _assert_entitlement(request)
     name = name.lower().strip().replace("-", " ")
     name = ALIASES.get(name, name)
     if name not in CITIES:
@@ -819,8 +860,9 @@ def _build_city_detail_payload(
 
 
 @app.get("/api/history/{name}")
-async def city_history(name: str):
+async def city_history(request: Request, name: str):
     """Return historical accuracy data (DEB, mu, actuals) for a city."""
+    _assert_entitlement(request)
     name = name.lower().strip().replace("-", " ")
     name = ALIASES.get(name, name)
     
@@ -854,7 +896,8 @@ async def city_history(name: str):
 
 
 @app.get("/api/city/{name}/summary")
-async def city_summary(name: str, force_refresh: bool = False):
+async def city_summary(request: Request, name: str, force_refresh: bool = False):
+    _assert_entitlement(request)
     city = _normalize_city_or_404(name)
     data = _analyze(city, force_refresh=force_refresh)
     return _build_city_summary_payload(data)
@@ -862,10 +905,12 @@ async def city_summary(name: str, force_refresh: bool = False):
 
 @app.get("/api/city/{name}/detail")
 async def city_detail_aggregate(
+    request: Request,
     name: str,
     force_refresh: bool = False,
     market_slug: Optional[str] = None,
 ):
+    _assert_entitlement(request)
     city = _normalize_city_or_404(name)
     data = _analyze(city, force_refresh=force_refresh)
     return _build_city_detail_payload(data, market_slug=market_slug)