From 901b8702408b15c9a0486c78dacaad95bad9853a Mon Sep 17 00:00:00 2001 From: "2569718930@qq.com" <2569718930@qq.com> Date: Sun, 26 Apr 2026 05:58:07 +0800 Subject: [PATCH] feat: implement scan terminal service with caching and add corresponding dashboard UI components --- .../dashboard/ScanTerminalDashboard.tsx | 55 +++++++++++++++++-- frontend/hooks/useDashboardStore.tsx | 11 ++-- web/scan_terminal_service.py | 29 ++++++++-- 3 files changed, 78 insertions(+), 17 deletions(-) diff --git a/frontend/components/dashboard/ScanTerminalDashboard.tsx b/frontend/components/dashboard/ScanTerminalDashboard.tsx index cba7f13e..c0545fa5 100644 --- a/frontend/components/dashboard/ScanTerminalDashboard.tsx +++ b/frontend/components/dashboard/ScanTerminalDashboard.tsx @@ -439,6 +439,33 @@ function findDetailForCity( ); } +function countDetailModels(detail?: CityDetail | null, targetDate?: string | null) { + if (!detail) return 0; + const date = String(targetDate || detail.local_date || "").trim(); + const dailyModels = date ? detail.multi_model_daily?.[date]?.models : null; + const models = + dailyModels && typeof dailyModels === "object" + ? dailyModels + : detail.multi_model || {}; + return Object.values(models).filter((value) => + Number.isFinite(Number(value)), + ).length; +} + +function countDetailForecastDays(detail?: CityDetail | null) { + const daily = detail?.forecast?.daily; + return Array.isArray(daily) ? daily.length : 0; +} + +function isFullEnoughForDeepAnalysis(detail?: CityDetail | null) { + if (!detail) return false; + if (detail.detail_depth && detail.detail_depth !== "full") return false; + return ( + countDetailModels(detail, detail.local_date) > 1 && + countDetailForecastDays(detail) > 1 + ); +} + function AiCityTemperatureChart({ detail }: { detail: CityDetail }) { const { locale } = useI18n(); const chartData = useMemo( @@ -1187,6 +1214,7 @@ function ScanTerminalScreen() { const [userLocalTime, setUserLocalTime] = useState("--"); const [themeMode, setThemeMode] = useState("dark"); const lastMapSelectedCityRef = useRef(""); + const aiFullHydrationRef = useRef>(new Set()); const timeSortedRows = useMemo( () => sortRowsByUserTime(terminalData?.rows || []), @@ -1376,7 +1404,18 @@ function ScanTerminalScreen() { } return [nextItem, ...current].slice(0, 8); }); - void store.ensureCityDetail(cleanName, false, "full").catch(() => {}); + aiFullHydrationRef.current.delete(key); + aiFullHydrationRef.current.add(key); + void store + .ensureCityDetail(cleanName, true, "full") + .then((detail) => { + if (!isFullEnoughForDeepAnalysis(detail)) { + aiFullHydrationRef.current.delete(key); + } + }) + .catch(() => { + aiFullHydrationRef.current.delete(key); + }); }, [locale, store.ensureCityDetail, timeSortedRows]); const removeAiPinnedCity = useCallback((cityName: string) => { @@ -1388,9 +1427,17 @@ function ScanTerminalScreen() { useEffect(() => { aiPinnedCities.forEach((item) => { - if (!findDetailForCity(store.cityDetailsByName, item.cityName)) { - void store.ensureCityDetail(item.cityName, false, "full").catch(() => {}); - } + const key = normalizeCityKey(item.cityName); + if (!key || aiFullHydrationRef.current.has(key)) return; + const detail = findDetailForCity(store.cityDetailsByName, item.cityName); + const needsFullHydration = !isFullEnoughForDeepAnalysis(detail); + if (!needsFullHydration) return; + aiFullHydrationRef.current.add(key); + void store + .ensureCityDetail(item.cityName, Boolean(detail), "full") + .catch(() => { + aiFullHydrationRef.current.delete(key); + }); }); }, [aiPinnedCities, store.cityDetailsByName, store.ensureCityDetail]); diff --git a/frontend/hooks/useDashboardStore.tsx b/frontend/hooks/useDashboardStore.tsx index 48b7a30d..84c591f9 100644 --- a/frontend/hooks/useDashboardStore.tsx +++ b/frontend/hooks/useDashboardStore.tsx @@ -841,9 +841,7 @@ export function DashboardStoreProvider({ return; } - if (!cached) { - setLoadingState((current) => ({ ...current, cityDetail: true })); - } + setLoadingState((current) => ({ ...current, cityDetail: !cached })); const detailPromise = ensureCityDetail(cityName, false, "panel"); void Promise.allSettled([summaryPromise, detailPromise]) .then(([, detail]) => { @@ -854,20 +852,19 @@ export function DashboardStoreProvider({ }) .finally(() => { if (selectedCityRef.current !== cityName) return; - if (!cached) { - setLoadingState((current) => ({ ...current, cityDetail: false })); - } + setLoadingState((current) => ({ ...current, cityDetail: false })); }); }; const focusCity = async (cityName: string) => { + const cached = cityDetailsByName[cityName]; selectedCityRef.current = cityName; setSelectedCity(cityName); setIsPanelOpen(false); setSelectedForecastDate(null); setFutureModalDate(null); setForecastModalMode(null); - setLoadingState((current) => ({ ...current, cityDetail: true })); + setLoadingState((current) => ({ ...current, cityDetail: !cached })); void Promise.allSettled([ ensureCitySummary(cityName), ensureCityDetail(cityName, false, "panel"), diff --git a/web/scan_terminal_service.py b/web/scan_terminal_service.py index 13fef342..2b29e0c8 100644 --- a/web/scan_terminal_service.py +++ b/web/scan_terminal_service.py @@ -66,6 +66,7 @@ SCAN_CITY_AI_MAX_TOKENS = max( 8192, int(os.getenv("POLYWEATHER_SCAN_CITY_AI_MAX_TOKENS", "8192")), ) +SCAN_CITY_AI_PROMPT_VERSION = "city-airport-read-v2" def _safe_float(value: Any) -> Optional[float]: @@ -996,7 +997,8 @@ def _build_city_ai_prompt(data: Dict[str, Any]) -> Dict[str, Any]: risk = data.get("risk") if isinstance(data.get("risk"), dict) else {} return { - "schema_version": "single_city_forecast_v1", + "schema_version": "single_city_forecast_v2", + "prompt_version": SCAN_CITY_AI_PROMPT_VERSION, "task": "predict_city_daily_high_and_read_metar", "city": data.get("name"), "city_display_name": data.get("display_name") or data.get("name"), @@ -1077,10 +1079,15 @@ def _call_deepseek_city_ai(ai_input: Dict[str, Any], *, locale: str = "zh-CN") - "如果实测温度与 DEB 预测走势出现偏差，要明确说明偏差方向和可能修正。" "你可以基于城市、时间、季节、机场位置、风向/风速、云、能见度、露点等判断风或天气是否可能影响温度路径，" "但必须使用“可能”“倾向”“需要确认”等非绝对表达。" + "METAR 解读必须具体：写清楚最新报文时间、温度、风向风速、云量/天气、能见度或露点中与温度路径相关的因素。" + "涉及风时必须说明该风向对本城市/机场最高温路径倾向增温、降温还是中性，并给出理由；" + "不得只写“风向切换可能冷平流”，必须说明是哪一类风向或哪段风向切换可能带来冷/暖平流。" + "涉及 TAF 或云雨扰动时必须给出报文中的有效时间、BECMG/TEMPO/FM 时间窗或说明“未给出明确时间”；" + "如果没有 TAF 时间依据，不要笼统写“峰值窗口云雨扰动风险”。" "如果峰值窗口尚未到来，不能过早下最终结论；如果峰值窗口已过或实测已创高，需要更重视 METAR 实测。" f"当前用户界面语言是 {normalized_locale}，所有面向用户的主要自然语言字段必须使用 {primary_language}。" f"重点填写 {primary_suffix} 字段；{secondary_suffix} 字段只填空字符串，前端不读取它。" - "risks 最多 2 条，每条不超过 18 个汉字或 12 个英文词；reasoning、metar_read、model_cluster_note 各 1 句。" + "risks 最多 2 条，每条必须包含触发条件或方向来源；reasoning、model_cluster_note 各 1 句，metar_read 可用 2-4 句。" "只返回 JSON object，不要 Markdown。" ) user_payload = { @@ -1092,8 +1099,12 @@ def _call_deepseek_city_ai(ai_input: Dict[str, Any], *, locale: str = "zh-CN") - "reasoning_zh, reasoning_en, risks_zh, risks_en, model_cluster_note_zh, model_cluster_note_en. " f"Primary output language is {primary_language}; the UI will read fields ending with {primary_suffix}. " f"Fields ending with {secondary_suffix} must be empty strings or empty arrays to avoid truncation. " - "Keep final_judgment one short decision sentence. metar_read should explain the latest airport bulletin " - "and how wind/cloud/visibility/dewpoint may affect the temperature path. model_cluster_note must state " + "Keep final_judgment one short decision sentence. metar_read must explain the latest airport bulletin " + "with report time, temperature, wind direction/speed, cloud/weather/visibility/dewpoint if available. " + "For wind, explicitly say whether the current wind tends to warm, cool, or be neutral for today's high, " + "and why in local city/airport context. If mentioning cold/warm advection, name the wind direction or " + "direction shift responsible. If mentioning TAF risk, include the concrete TAF time window or say no " + "explicit timing is available. model_cluster_note must state " "how many model sources are available, whether they support DEB, and whether the sample is too sparse. " "Keep the whole JSON compact." ), @@ -1238,7 +1249,11 @@ def _call_deepseek_city_ai(ai_input: Dict[str, Any], *, locale: str = "zh-CN") - "instruction": ( f"Primary UI language is {primary_language}. " "Make final_judgment one direct sentence about today's high temperature. " - "metar_read must interpret the latest airport bulletin and possible temperature-path impact. " + "metar_read must interpret the latest airport bulletin with report time, temperature, " + "wind direction/speed, cloud/weather/visibility/dewpoint if available. State whether " + "the current wind tends to warm, cool, or stay neutral for the temperature path, and why. " + "If mentioning cold/warm advection or TAF risk, include the responsible wind direction " + "or the concrete TAF time window; otherwise say timing is not explicit. " "model_cluster_note must mention available model count/range and whether it supports DEB. " "Keep the JSON compact." ), @@ -1287,6 +1302,8 @@ def _call_deepseek_city_ai(ai_input: Dict[str, Any], *, locale: str = "zh-CN") - def _scan_city_ai_cache_key(ai_input: Dict[str, Any]) -> str: key_payload = { + "prompt_version": SCAN_CITY_AI_PROMPT_VERSION, + "schema_version": ai_input.get("schema_version"), "city": ai_input.get("city"), "local_date": ai_input.get("local_date"), "local_time": ai_input.get("local_time"), @@ -1331,7 +1348,7 @@ def build_scan_city_ai_forecast_payload( normalized_locale, SCAN_AI_MODEL, ) - cache_key = f"city_forecast:{city_name.lower()}:{normalized_locale}" + cache_key = f"city_forecast:{SCAN_CITY_AI_PROMPT_VERSION}:{city_name.lower()}:{normalized_locale}" if not force_refresh: with _SCAN_CITY_AI_CACHE_LOCK: cached = _SCAN_CITY_AI_CACHE.get(cache_key)