feat: implement AI-driven METAR summary service and dashboard UI components

.env.example

@@ -142,13 +142,16 @@ POLYWEATHER_DEEPSEEK_API_KEY=
 POLYWEATHER_DEEPSEEK_BASE_URL=https://api.deepseek.com
 POLYWEATHER_SCAN_AI_MODEL=deepseek-v4-pro
 POLYWEATHER_SCAN_CITY_AI_MODEL=deepseek-v4-flash
+POLYWEATHER_METAR_SUMMARY_AI_MODEL=deepseek-v4-flash
 POLYWEATHER_SCAN_AI_TIMEOUT_SEC=40
 POLYWEATHER_SCAN_CITY_AI_TIMEOUT_SEC=18
+POLYWEATHER_METAR_SUMMARY_AI_TIMEOUT_SEC=8
 POLYWEATHER_SCAN_CITY_AI_RETRY_ON_STREAM_PARSE_ERROR=false
 POLYWEATHER_SCAN_AI_CACHE_TTL_SEC=1800
 POLYWEATHER_SCAN_AI_MAX_ROWS=40
 POLYWEATHER_SCAN_AI_MAX_TOKENS=3200
 POLYWEATHER_SCAN_CITY_AI_MAX_TOKENS=900
+POLYWEATHER_METAR_SUMMARY_AI_MAX_TOKENS=160
 POLYWEATHER_SCAN_AI_PROXY_TIMEOUT_MS=55000
 POLYWEATHER_PREWARM_CITIES=ankara,istanbul,shanghai,beijing,shenzhen,guangzhou,wuhan,chengdu,chongqing,hong kong,taipei,singapore,tokyo,seoul,busan,london,paris,madrid
 POLYWEATHER_CITY_SUMMARY_CACHE_TTL_SEC=1800

frontend/app/api/ai/metar-summary/route.ts

@@ -0,0 +1,69 @@
+import { NextRequest, NextResponse } from "next/server";
+import {
+  applyAuthResponseCookies,
+  buildBackendRequestHeaders,
+} from "@/lib/backend-auth";
+
+const API_BASE = process.env.POLYWEATHER_API_BASE_URL;
+
+export const dynamic = "force-dynamic";
+export const maxDuration = 30;
+
+export async function POST(req: NextRequest) {
+  if (!API_BASE) {
+    return NextResponse.json(
+      { error: "POLYWEATHER_API_BASE_URL is not configured" },
+      { status: 500 },
+    );
+  }
+
+  let body: unknown = {};
+  try {
+    body = await req.json();
+  } catch {
+    body = {};
+  }
+
+  const requestBody =
+    body && typeof body === "object" ? (body as Record<string, unknown>) : {};
+  const auth = await buildBackendRequestHeaders(req);
+  const headers = new Headers(auth.headers);
+  headers.set("Content-Type", "application/json");
+  headers.set("Accept", "text/event-stream");
+
+  try {
+    const res = await fetch(`${API_BASE}/api/ai/metar-summary`, {
+      method: "POST",
+      headers,
+      cache: "no-store",
+      body: JSON.stringify(requestBody),
+    });
+    if (!res.ok || !res.body) {
+      const raw = await res.text();
+      const response = NextResponse.json(
+        { error: `Backend returned ${res.status}`, detail: raw.slice(0, 300) },
+        { status: res.status === 402 || res.status === 403 ? res.status : 502 },
+      );
+      return applyAuthResponseCookies(response, auth.response);
+    }
+
+    const response = new NextResponse(res.body, {
+      status: 200,
+      headers: {
+        "Content-Type": "text/event-stream; charset=utf-8",
+        "Cache-Control": "no-store, no-transform",
+        "X-Accel-Buffering": "no",
+      },
+    });
+    return applyAuthResponseCookies(response, auth.response);
+  } catch (error) {
+    const response = NextResponse.json(
+      {
+        error: "Failed to stream METAR summary",
+        detail: String(error),
+      },
+      { status: 500 },
+    );
+    return applyAuthResponseCookies(response, auth.response);
+  }
+}

frontend/components/dashboard/scan-terminal/AiPinnedForecastView.tsx

@@ -16,6 +16,7 @@ import { LoadingSignal } from "@/components/dashboard/scan-terminal/LoadingSigna
 import type { AiPinnedCity } from "@/components/dashboard/scan-terminal/types";
 import {
   useAiCityForecast,
+  useAiMetarSummary,
   useCityMarketScan,
 } from "@/components/dashboard/scan-terminal/use-ai-city-card-data";
 import type { CityDetail, ScanOpportunityRow } from "@/lib/dashboard-types";
@@ -152,6 +153,20 @@ function AiPinnedCityCard({
     detail?.airport_primary?.station_code ||
     "";
   const detailCityName = detail?.name || item.cityName;
+  const debText =
+    debNumber != null
+      ? formatTemperatureValue(debNumber, tempSymbol, { digits: 1 })
+      : "";
+  const { metarSummary } = useAiMetarSummary({
+    airport: airportStation,
+    city: displayName,
+    deb: debText,
+    enabled: Boolean(detail && report),
+    isEn,
+    locale,
+    metar: report,
+    modelRange,
+  });
   const { aiForecast, refreshAiForecast } = useAiCityForecast({
     detail,
     detailCityName,
@@ -249,7 +264,6 @@ function AiPinnedCityCard({
       ? [String(localizedRisksRaw)]
       : [];
   const aiBullets = [
-    localizedMetarRead,
     localizedReasoning !== localizedFinalJudgment ? localizedReasoning : "",
     localizedModelNote || localModelSupportNote,
     ...localizedRisks,
@@ -420,21 +434,66 @@ function AiPinnedCityCard({
               <div className="scan-ai-city-section-title">
                 {isEn ? "Evidence · AI airport read" : "证据 · AI 机场报文解读"}
               </div>
+              {metarSummary.status === "loading" ? (
+                <>
+                  <p className="scan-ai-weather-summary">
+                    {metarSummary.streamText ||
+                      (isEn
+                        ? "Streaming the lightweight METAR read..."
+                        : "轻量 METAR 解读正在流式输出…")}
+                  </p>
+                  <p className="scan-ai-city-muted">
+                    {isEn
+                      ? "This read is independent from the full city review below."
+                      : "这一步已和下方完整城市分析解耦，不等待完整 JSON。"}
+                  </p>
+                </>
+              ) : metarSummary.status === "ready" && metarSummary.streamText ? (
+                <p className="scan-ai-weather-summary">{metarSummary.streamText}</p>
+              ) : metarSummary.status === "failed" ? (
+                <p>
+                  {localizedMetarRead ||
+                    (isEn
+                      ? "Lightweight AI METAR read is unavailable; raw METAR remains below."
+                      : "轻量 AI METAR 解读暂不可用；下方保留原始 METAR。")}
+                </p>
+              ) : (
+                <p>
+                  {report
+                    ? isEn
+                      ? "Waiting for lightweight AI to read the latest METAR."
+                      : "等待轻量 AI 解读最新 METAR。"
+                    : isEn
+                      ? "Raw METAR is unavailable."
+                      : "暂无原始 METAR。"}
+                </p>
+              )}
+              <p className="scan-ai-raw-metar">
+                {report
+                  ? `${isEn ? "Raw METAR" : "原始 METAR"}：${`${airportStation} ${report}`.trim()}`
+                  : isEn
+                    ? "Raw METAR: unavailable."
+                    : "原始 METAR：暂无。"}
+              </p>
+            </section>
+            <section className="scan-ai-city-section">
+              <div className="scan-ai-city-section-title">
+                {isEn ? "Complete city AI review" : "完整城市 AI 判断"}
+              </div>
               {aiForecast.status === "loading" ? (
                 <>
                   <p className={aiForecast.streamText ? "scan-ai-weather-summary" : undefined}>
-                    {aiForecast.streamText ||
+                    {localizedFinalJudgment ||
+                      aiForecast.streamText ||
                       (isEn
-                        ? "DeepSeek is reading the latest airport bulletin..."
+                        ? "Generating the full city review in the background..."
-                        : "DeepSeek 正在解读最新机场报文...")}
+                        : "后台正在生成完整城市分析…")}
+                  </p>
+                  <p className="scan-ai-city-muted">
+                    {isEn
+                      ? "This heavier JSON review can finish after the airport read."
+                      : "这部分是较重的 JSON 分析，可以晚于机场报文解读完成。"}
                   </p>
-                  {!aiForecast.streamText ? (
-                    <p className="scan-ai-city-muted">
-                      {isEn
-                        ? "The final airport read will appear here shortly."
-                        : "机场报文解读稍后将在这里显示。"}
-                    </p>
-                  ) : null}
                 </>
               ) : aiForecast.status === "ready" && aiCityForecast ? (
                 <>
@@ -447,13 +506,6 @@ function AiPinnedCityCard({
                       <li key={`${line}-${index}`}>{line}</li>
                     ))}
                   </ul>
-                  <p className="scan-ai-raw-metar">
-                    {report
-                      ? `${isEn ? "Raw METAR" : "原始 METAR"}：${`${airportStation} ${report}`.trim()}`
-                      : isEn
-                        ? "Raw METAR: unavailable."
-                        : "原始 METAR：暂无。"}
-                  </p>
                 </>
               ) : aiForecast.status === "ready" ? (
                 <>
@@ -469,13 +521,6 @@ function AiPinnedCityCard({
                   </p>
                   <ul className="scan-ai-weather-bullets">
                     <li>{localModelSupportNote}</li>
-                    <li>
-                      {report
-                        ? `${isEn ? "Raw METAR" : "原始 METAR"}：${`${airportStation} ${report}`.trim()}`
-                        : isEn
-                          ? "Raw METAR is unavailable."
-                          : "暂无原始 METAR。"}
-                    </li>
                   </ul>
                 </>
               ) : aiForecast.status === "failed" ? (
@@ -488,20 +533,13 @@ function AiPinnedCityCard({
                   </p>
                   <ul className="scan-ai-weather-bullets">
                     <li>{localModelSupportNote}</li>
-                    <li>
-                      {report
-                        ? `${isEn ? "Raw METAR" : "原始 METAR"}：${`${airportStation} ${report}`.trim()}`
-                        : isEn
-                          ? "Raw METAR is unavailable."
-                          : "暂无原始 METAR。"}
-                    </li>
                   </ul>
                 </>
               ) : (
                 <p>
                   {isEn
-                    ? "Waiting for AI to read the latest airport bulletin."
+                    ? "The complete city review is queued in the background."
-                    : "等待 AI 解读最新机场报文。"}
+                    : "完整城市分析正在后台排队。"}
                 </p>
               )}
             </section>

frontend/components/dashboard/scan-terminal/types.ts

@@ -39,3 +39,20 @@ export type AiCityForecastState = {
   streamRaw?: string | null;
 };
 
+export type AiMetarSummaryPayload = {
+  status?: string | null;
+  summary?: string | null;
+  reason?: string | null;
+  degraded?: boolean | null;
+  duration_ms?: number | null;
+  model?: string | null;
+  provider?: string | null;
+};
+
+export type AiMetarSummaryState = {
+  status: "idle" | "loading" | "ready" | "failed";
+  payload?: AiMetarSummaryPayload | null;
+  error?: string | null;
+  streamText?: string | null;
+};
+

frontend/components/dashboard/scan-terminal/use-ai-city-card-data.ts

@@ -4,6 +4,8 @@ import { useCallback, useEffect, useMemo, useState } from "react";
 import type {
   AiCityForecastPayload,
   AiCityForecastState,
+  AiMetarSummaryPayload,
+  AiMetarSummaryState,
 } from "@/components/dashboard/scan-terminal/types";
 import { useDashboardStore } from "@/hooks/useDashboardStore";
 import {
@@ -22,6 +24,10 @@ const pendingAiCityForecastRequests = new Map<
   string,
   Promise<AiCityForecastPayload>
 >();
+const pendingMetarSummaryRequests = new Map<
+  string,
+  Promise<AiMetarSummaryPayload>
+>();
 
 type AiCityStreamProgress = {
   stage?: string | null;
@@ -39,6 +45,13 @@ type AiCityStreamEvent = {
   event: string;
 };
 
+type AiMetarSummaryProgress = {
+  message_en?: string | null;
+  message_zh?: string | null;
+  content?: string | null;
+  raw_length?: number | null;
+};
+
 function getStorage() {
   if (typeof window === "undefined") return null;
   try {
@@ -270,6 +283,118 @@ function getAiCityStreamProgressText(progress: AiCityStreamProgress, isEn: boole
   return "";
 }
 
+async function readMetarSummaryStream(
+  response: Response,
+  onProgress?: (progress: AiMetarSummaryProgress) => void,
+) {
+  if (!response.body) {
+    return response.json() as Promise<AiMetarSummaryPayload>;
+  }
+
+  const reader = response.body.getReader();
+  const decoder = new TextDecoder();
+  let buffer = "";
+  let accumulated = "";
+  let finalPayload: AiMetarSummaryPayload | null = null;
+
+  const consumeBlock = (block: string) => {
+    const parsed = parseAiCityStreamBlock(block);
+    if (!parsed) return;
+    const { data, event } = parsed;
+    if (event === "final") {
+      finalPayload = data as AiMetarSummaryPayload;
+      return;
+    }
+    if (event === "progress") {
+      onProgress?.(data as AiMetarSummaryProgress);
+      return;
+    }
+    if (event === "delta") {
+      const content = String(data.content || "");
+      if (content) {
+        accumulated += content;
+      }
+      onProgress?.({
+        content: accumulated,
+        raw_length: Number(data.raw_length),
+      });
+    }
+  };
+
+  for (;;) {
+    const { done, value } = await reader.read();
+    buffer += decoder.decode(value || new Uint8Array(), { stream: !done });
+    const blocks = buffer.split(/\r?\n\r?\n/);
+    buffer = blocks.pop() || "";
+    blocks.forEach(consumeBlock);
+    if (done) break;
+  }
+  if (buffer.trim()) {
+    consumeBlock(buffer);
+  }
+  return (
+    finalPayload || {
+      status: accumulated ? "ready" : "failed",
+      summary: accumulated,
+    }
+  );
+}
+
+function requestMetarSummary({
+  airport,
+  city,
+  deb,
+  locale,
+  metar,
+  modelRange,
+  onProgress,
+  requestKey,
+}: {
+  airport: string;
+  city: string;
+  deb: string;
+  locale: string;
+  metar: string;
+  modelRange: string;
+  onProgress?: (progress: AiMetarSummaryProgress) => void;
+  requestKey: string;
+}) {
+  const pending = pendingMetarSummaryRequests.get(requestKey);
+  if (pending) return pending;
+
+  const request = buildBrowserBackendHeaders({
+    Accept: "text/event-stream",
+    "Content-Type": "application/json",
+  })
+    .then((headers) =>
+      fetchBackendApi("/api/ai/metar-summary", {
+        method: "POST",
+        headers,
+        cache: "no-store",
+        body: JSON.stringify({
+          airport,
+          city,
+          deb,
+          locale,
+          metar,
+          model_range: modelRange,
+        }),
+      }),
+    )
+    .then(async (response) => {
+      if (!response.ok) {
+        throw new Error(`HTTP ${response.status}`);
+      }
+      return readMetarSummaryStream(response, onProgress);
+    })
+    .finally(() => {
+      pendingMetarSummaryRequests.delete(requestKey);
+    });
+
+  pendingMetarSummaryRequests.set(requestKey, request);
+  return request;
+}
+
 function buildAiCityFallbackPayload({
   detail,
   error,
@@ -337,6 +462,113 @@ function buildAiCityFallbackPayload({
   };
 }
 
+export function useAiMetarSummary({
+  airport,
+  city,
+  deb,
+  enabled = true,
+  isEn,
+  locale,
+  metar,
+  modelRange,
+}: {
+  airport: string;
+  city: string;
+  deb: string;
+  enabled?: boolean;
+  isEn: boolean;
+  locale: string;
+  metar: string;
+  modelRange: string;
+}) {
+  const [metarSummary, setMetarSummary] = useState<AiMetarSummaryState>({
+    status: "idle",
+  });
+
+  const requestKey = useMemo(
+    () =>
+      metar
+        ? [
+            "metar-summary",
+            normalizeCityKey(city) || city,
+            airport,
+            locale,
+            deb,
+            modelRange,
+            metar,
+          ].join(":")
+        : "",
+    [airport, city, deb, locale, metar, modelRange],
+  );
+
+  useEffect(() => {
+    if (!enabled || !requestKey || !metar) {
+      setMetarSummary({ status: "idle" });
+      return;
+    }
+    let cancelled = false;
+    setMetarSummary({
+      status: "loading",
+      streamText: isEn
+        ? "Reading current METAR with a lightweight AI pass..."
+        : "正在用轻量 AI 快速解读当前 METAR…",
+    });
+    void requestMetarSummary({
+      airport,
+      city,
+      deb,
+      locale,
+      metar,
+      modelRange,
+      onProgress: (progress) => {
+        if (cancelled) return;
+        const text = String(
+          progress.content ||
+            (isEn ? progress.message_en : progress.message_zh) ||
+            "",
+        ).trim();
+        if (!text) return;
+        setMetarSummary((current) => ({
+          ...current,
+          status: "loading",
+          streamText: text,
+        }));
+      },
+      requestKey,
+    })
+      .then((payload) => {
+        if (cancelled) return;
+        const summary = String(payload?.summary || "").trim();
+        if (summary) {
+          setMetarSummary({
+            payload,
+            status: "ready",
+            streamText: summary,
+          });
+        } else {
+          setMetarSummary({
+            payload,
+            status: "failed",
+            error: String(payload?.reason || payload?.status || "empty response"),
+          });
+        }
+      })
+      .catch((error) => {
+        if (!cancelled) {
+          setMetarSummary({
+            status: "failed",
+            error: String(error),
+          });
+        }
+      });
+    return () => {
+      cancelled = true;
+    };
+  }, [airport, city, deb, enabled, isEn, locale, metar, modelRange, requestKey]);
+
+  return { metarSummary };
+}
+
 export function useAiCityForecast({
   detail,
   detailCityName,

web/routes.py

@@ -36,6 +36,7 @@ from web.scan_terminal_service import (
     build_scan_city_ai_forecast_payload,
     build_scan_terminal_ai_payload,
     build_scan_terminal_payload,
+    stream_metar_summary_payload,
     stream_scan_city_ai_forecast_payload,
 )
 from web.core import (
@@ -1811,3 +1812,21 @@ async def scan_terminal_ai_city_stream(request: Request):
         },
     )
 
+
+@router.post("/api/ai/metar-summary")
+async def ai_metar_summary_stream(request: Request):
+    _assert_entitlement(request)
+    try:
+        body = await request.json()
+    except Exception:
+        body = {}
+    if not isinstance(body, dict):
+        raise HTTPException(status_code=400, detail="Invalid JSON body")
+    return StreamingResponse(
+        stream_metar_summary_payload(body),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-store",
+            "X-Accel-Buffering": "no",
+        },
+    )

web/scan_terminal_service.py

@@ -98,6 +98,24 @@ SCAN_CITY_AI_MAX_TOKENS = _env_int(
     min_value=800,
     max_value=64000,
 )
+METAR_SUMMARY_AI_MODEL = str(
+    os.getenv("POLYWEATHER_METAR_SUMMARY_AI_MODEL")
+    or os.getenv("POLYWEATHER_SCAN_CITY_AI_MODEL")
+    or os.getenv("POLYWEATHER_SCAN_AI_MODEL")
+    or "deepseek-v4-flash"
+).strip()
+METAR_SUMMARY_AI_TIMEOUT_SEC = _env_int(
+    "POLYWEATHER_METAR_SUMMARY_AI_TIMEOUT_SEC",
+    8,
+    min_value=3,
+    max_value=30,
+)
+METAR_SUMMARY_AI_MAX_TOKENS = _env_int(
+    "POLYWEATHER_METAR_SUMMARY_AI_MAX_TOKENS",
+    160,
+    min_value=80,
+    max_value=1000,
+)
 SCAN_CITY_AI_PROMPT_VERSION = "city-airport-read-v3"
 
 CITY_AI_REQUIRED_FIELDS = [
@@ -627,14 +645,25 @@ def _build_city_ai_fallback(
     if partial_ai.get("final_judgment_zh") or partial_ai.get("final_judgment_en"):
         final_zh = str(partial_ai.get("final_judgment_zh") or partial_ai.get("final_judgment_en") or "").strip()
         final_en = str(partial_ai.get("final_judgment_en") or partial_ai.get("final_judgment_zh") or "").strip()
+    elif partial_ai:
+        final_zh = f"{city} 预计最高温暂以 {predicted_text} 附近为中枢；AI 已先完成机场报文解读，最高温结论结合 DEB、多模型与最新 METAR 校准。"
+        final_en = f"{city} daily high is centered near {predicted_text}; AI has already read the airport bulletin, with the high calibrated against DEB, the model cluster and latest METAR."
     elif timed_out:
         final_zh = f"{city} 预计最高温暂以 {predicted_text} 附近为中枢；当前已先用 DEB、多模型和 METAR 快速证据模式判断。"
         final_en = f"{city} daily high is centered near {predicted_text}; the current read uses the fast DEB/model/METAR evidence mode."
     else:
         final_zh = f"{city} 预计最高温暂以 {predicted_text} 附近为中枢；当前已先用 DEB、多模型和 METAR 快速证据模式判断。"
         final_en = f"{city} daily high is centered near {predicted_text}; the current read uses the fast DEB/model/METAR evidence mode."
-    reasoning_zh = str(partial_ai.get("reasoning_zh") or "").strip() or "DEB、多模型集合和最新 METAR 已足够给出当前方向判断；AI 增强可作为后续补充，不阻塞本轮读数。"
+    reasoning_zh = str(partial_ai.get("reasoning_zh") or "").strip() or (
-    reasoning_en = str(partial_ai.get("reasoning_en") or "").strip() or "DEB, the model cluster and latest METAR are enough for the current directional read; AI enhancement can be added later without blocking this card."
+        "AI 机场报文解读已用于校准日内节奏；DEB 与多模型集合继续约束最高温中枢，后续 METAR 用于确认是否需要上调或下修。"
+        if partial_ai
+        else "DEB、多模型集合和最新 METAR 已足够给出当前方向判断；AI 增强可作为后续补充，不阻塞本轮读数。"
+    )
+    reasoning_en = str(partial_ai.get("reasoning_en") or "").strip() or (
+        "The AI airport-bulletin read is already used to calibrate the intraday pace; DEB and the model cluster still constrain the high-temperature center, while later METAR reports confirm whether to revise it."
+        if partial_ai
+        else "DEB, the model cluster and latest METAR are enough for the current directional read; AI enhancement can be added later without blocking this card."
+    )
     risks_zh = ["后续 METAR 若明显偏离模型路径，需及时修正最高温中枢。"]
     risks_en = ["If later METAR reports diverge from the model path, revise the daily-high center promptly."]
     return {
@@ -1750,6 +1779,177 @@ def _build_city_ai_stream_request(
     }
 
 
+def stream_metar_summary_payload(body: Dict[str, Any]) -> Iterator[str]:
+    """Stream a tiny METAR-only AI read.
+
+    This intentionally does not share the full city-review prompt. The goal is
+    first-token speed for the "AI airport read" section, while the heavier city
+    JSON review continues separately.
+    """
+
+    started_at = time.time()
+    normalized_locale = _normalize_locale(str(body.get("locale") or "zh-CN"))
+    city = str(body.get("city") or "").strip()
+    airport = str(body.get("airport") or body.get("station") or "").strip()
+    metar = str(body.get("metar") or "").strip()
+    model_range = str(body.get("model_range") or "").strip()
+    deb = str(body.get("deb") or "").strip()
+
+    if not metar:
+        yield _sse_event(
+            "final",
+            {
+                "status": "failed",
+                "model": METAR_SUMMARY_AI_MODEL,
+                "provider": "deepseek",
+                "summary": "",
+                "reason": "metar is required",
+                "duration_ms": int((time.time() - started_at) * 1000),
+            },
+        )
+        return
+
+    yield _sse_event(
+        "progress",
+        {
+            "stage": "calling_ai",
+            "message_zh": "DeepSeek 正在快速解读当前 METAR…",
+            "message_en": "DeepSeek is quickly reading the current METAR…",
+        },
+    )
+
+    if not SCAN_AI_ENABLED:
+        yield _sse_event(
+            "final",
+            {
+                "status": "disabled",
+                "model": METAR_SUMMARY_AI_MODEL,
+                "provider": "deepseek",
+                "summary": "",
+                "reason": "POLYWEATHER_SCAN_AI_ENABLED is not enabled",
+                "duration_ms": int((time.time() - started_at) * 1000),
+            },
+        )
+        return
+    if not str(os.getenv("POLYWEATHER_DEEPSEEK_API_KEY") or "").strip():
+        yield _sse_event(
+            "final",
+            {
+                "status": "missing_key",
+                "model": METAR_SUMMARY_AI_MODEL,
+                "provider": "deepseek",
+                "summary": "",
+                "reason": "POLYWEATHER_DEEPSEEK_API_KEY is not configured",
+                "duration_ms": int((time.time() - started_at) * 1000),
+            },
+        )
+        return
+
+    is_en = normalized_locale == "en-US"
+    system_prompt = (
+        "You are PolyWeather's fast airport-bulletin module. "
+        "Use only the current METAR, DEB and model range. "
+        "Do not output JSON. Do not repeat the full METAR. Do not predict market prices. "
+        "Keep the answer within 80 Chinese characters or 45 English words."
+        if is_en
+        else "你是 PolyWeather 的机场报文快速解读模块。"
+        "请用中文用1到2句话解读当前 METAR 对今日最高温判断的影响。"
+        "要求：只基于当前 METAR、DEB 和模型区间；不输出 JSON；不要复述完整报文；"
+        "不要预测市场价格；不超过80个中文字。"
+    )
+    user_prompt = (
+        f"City: {city or 'unknown'}\n"
+        f"Airport: {airport or 'unknown'}\n"
+        f"METAR: {metar}\n"
+        f"DEB: {deb or 'unknown'}\n"
+        f"Model range: {model_range or 'unknown'}"
+    )
+    request_json = {
+        "model": METAR_SUMMARY_AI_MODEL,
+        "temperature": 0.15,
+        "max_tokens": METAR_SUMMARY_AI_MAX_TOKENS,
+        "stream": True,
+        "messages": [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_prompt},
+        ],
+    }
+    timeout = httpx.Timeout(
+        timeout=float(METAR_SUMMARY_AI_TIMEOUT_SEC),
+        connect=min(5.0, float(METAR_SUMMARY_AI_TIMEOUT_SEC)),
+        read=float(METAR_SUMMARY_AI_TIMEOUT_SEC),
+        write=5.0,
+        pool=3.0,
+    )
+    headers = {
+        "Authorization": f"Bearer {os.getenv('POLYWEATHER_DEEPSEEK_API_KEY')}",
+        "Content-Type": "application/json",
+    }
+    accumulated = ""
+    try:
+        logger.info(
+            "metar summary stream request city={} airport={} model={} timeout_sec={}",
+            city,
+            airport,
+            METAR_SUMMARY_AI_MODEL,
+            METAR_SUMMARY_AI_TIMEOUT_SEC,
+        )
+        with httpx.Client(timeout=timeout) as client:
+            with client.stream(
+                "POST",
+                f"{SCAN_AI_BASE_URL}/chat/completions",
+                headers=headers,
+                json=request_json,
+            ) as response:
+                response.raise_for_status()
+                for line in response.iter_lines():
+                    text = str(line or "").strip()
+                    if not text or not text.startswith("data:"):
+                        continue
+                    payload_text = text[5:].strip()
+                    if payload_text == "[DONE]":
+                        break
+                    try:
+                        chunk = json.loads(payload_text)
+                    except Exception:
+                        continue
+                    delta = _extract_provider_stream_delta(chunk)
+                    if delta:
+                        accumulated += delta
+                        yield _sse_event(
+                            "delta",
+                            {
+                                "content": delta,
+                                "raw_length": len(accumulated),
+                            },
+                        )
+        summary = _truncate_ai_text(accumulated, 260)
+        yield _sse_event(
+            "final",
+            {
+                "status": "ready" if summary else "empty",
+                "model": METAR_SUMMARY_AI_MODEL,
+                "provider": "deepseek",
+                "summary": summary,
+                "duration_ms": int((time.time() - started_at) * 1000),
+            },
+        )
+    except Exception as exc:
+        summary = _truncate_ai_text(accumulated, 260)
+        yield _sse_event(
+            "final",
+            {
+                "status": "ready" if summary else "failed",
+                "degraded": bool(summary),
+                "model": METAR_SUMMARY_AI_MODEL,
+                "provider": "deepseek",
+                "summary": summary,
+                "reason": str(exc),
+                "duration_ms": int((time.time() - started_at) * 1000),
+            },
+        )
+
+
 def _cache_city_ai_payload(
     cache_key: str,
     *,