MiMo AI 能力扩展：TAF解读、概率分布解读、异常检测、市场概览

AI 解读字段扩展:
    - 新增 taf_read_zh/en：解读机场预报中影响今日峰值窗口的变化
    - 新增 probability_read_zh/en：描述概率分布形态（最高桶、偏左/偏右）
    - stream max_tokens 900→1200 容纳新输出字段
    - 缓存 key 简化为 METAR原文+观测时间，大幅提升命中率
    - 兜底函数补全 TAF 和概率字段的确定性生成

    异常检测:
    - 纯数学计算，零 AI 延迟：实测温度 vs 全部模型预测上下限
    - 三级告警：breakout_above / breakout_below / deviation

    市场概览:
    - 新增 POST /api/scan/terminal/overview（MiMo 批量解读，缓存10分钟）
    - 前端 MarketOverviewBanner 可折叠横幅（顶栏与标签栏之间）
    - 移动端适配 640px/768px 断点，暗色/亮色双主题

    Scope-risk: MEDIUM — 170 测试通过，TypeScript 零错误，ruff 零告警
    Tested: python -m pytest -q (170 passed), npx tsc --noEmit (0 errors), ruff check .

web/services/market_overview_api.py

@@ -0,0 +1,196 @@
+"""Market overview — AI summary of all scan terminal rows, cached 10 min."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import threading
+import time
+from datetime import datetime
+from typing import Any, Dict, List
+
+from loguru import logger
+
+from web.scan_city_ai_helpers import _safe_float
+from web.scan_terminal_service import (
+    SCAN_AI_BASE_URL,
+    SCAN_CITY_AI_MODEL,
+    SCAN_CITY_AI_TIMEOUT_SEC,
+    _scan_ai_api_key,
+)
+
+_OVERVIEW_CACHE: Dict[str, Dict[str, Any]] = {}
+_OVERVIEW_CACHE_LOCK = threading.Lock()
+_OVERVIEW_MAX_TOKENS = 600
+_OVERVIEW_CACHE_TTL_SEC = 600
+
+
+def _build_overview_ai_request(
+    rows: List[Dict[str, Any]],
+    locale: str,
+) -> Dict[str, Any]:
+    cities = []
+    for row in rows:
+        if not isinstance(row, dict):
+            continue
+        city = row.get("city") or row.get("name") or ""
+        if not city:
+            continue
+        model_cluster = row.get("model_cluster") if isinstance(row.get("model_cluster"), dict) else {}
+        sources = model_cluster.get("sources") if isinstance(model_cluster.get("sources"), list) else []
+        values = [
+            _safe_float(s.get("value"))
+            for s in sources
+            if isinstance(s, dict) and _safe_float(s.get("value")) is not None
+        ]
+        deb_val = _safe_float(row.get("deb_prediction") or (row.get("deb") or {}).get("prediction"))
+        cities.append(
+            {
+                "city": str(city),
+                "display_name": row.get("display_name") or str(city),
+                "local_date": row.get("local_date", ""),
+                "deb": deb_val,
+                "model_min": min(values) if values else None,
+                "model_max": max(values) if values else None,
+                "model_count": len(values),
+                "current_temp": _safe_float(row.get("current_temp") or (row.get("current") or {}).get("temp")),
+                "max_so_far": _safe_float(row.get("current_max_so_far") or row.get("max_so_far") or (row.get("current") or {}).get("max_so_far")),
+                "risk_level": row.get("risk_level", ""),
+                "temp_unit": row.get("temp_unit") or row.get("temp_symbol") or "°C",
+            }
+        )
+
+    system_prompt = (
+        "你是 PolyWeather 的天气市场概览员。基于全部城市的扫描数据，写一段今日市场概览。"
+        "用 3-5 句概括：整体模型一致性、最值得关注的城市（模型分歧大或实测偏离集群）、异常信号。"
+        "highlights 最多 5 个城市，每个城市一句话点出关键信号。"
+        "只返回 JSON object，不要 Markdown。所有 *_zh 字段写简体中文，*_en 字段写英文。"
+    )
+    task = (
+        "Return JSON: overview_zh, overview_en, highlights (array of {city, note_zh, note_en}, max 5). "
+        "overview: 3-5 sentences covering model consensus, top divergence cities, anomalies. "
+        "highlights: per-city one-sentence signal. Keep compact."
+    )
+
+    return {
+        "model": SCAN_CITY_AI_MODEL,
+        "temperature": 0.3,
+        "max_tokens": _OVERVIEW_MAX_TOKENS,
+        "response_format": {"type": "json_object"},
+        "messages": [
+            {"role": "system", "content": system_prompt},
+            {
+                "role": "user",
+                "content": json.dumps(
+                    {
+                        "locale": locale,
+                        "task": task,
+                        "city_count": len(cities),
+                        "cities": cities,
+                    },
+                    ensure_ascii=False,
+                    default=str,
+                ),
+            },
+        ],
+    }
+
+
+def _cache_key(rows: List[Dict[str, Any]], locale: str) -> str:
+    finger = {
+        "city_ids": sorted(
+            row.get("city") or row.get("name") or ""
+            for row in rows
+            if isinstance(row, dict)
+        ),
+        "locale": locale,
+    }
+    raw = json.dumps(finger, sort_keys=True, ensure_ascii=False, default=str)
+    return "overview:" + hashlib.sha256(raw.encode("utf-8")).hexdigest()
+
+
+def build_market_overview_payload(
+    rows: List[Dict[str, Any]],
+    *,
+    locale: str = "zh-CN",
+    force_refresh: bool = False,
+) -> Dict[str, Any]:
+    if not rows:
+        return {"overview_zh": "", "overview_en": "", "highlights": [], "generated_at": None}
+
+    key = _cache_key(rows, locale)
+    if not force_refresh:
+        with _OVERVIEW_CACHE_LOCK:
+            cached = _OVERVIEW_CACHE.get(key)
+            if cached and cached.get("expires_at", 0) >= time.time():
+                return cached["payload"]
+
+    api_key = _scan_ai_api_key()
+    if not api_key:
+        return {
+            "overview_zh": "AI 概览不可用（未配置 API Key）",
+            "overview_en": "AI overview unavailable (API key not configured)",
+            "highlights": [],
+            "generated_at": datetime.utcnow().isoformat() + "Z",
+        }
+
+    import httpx
+
+    request_json = _build_overview_ai_request(rows, locale)
+    generated_at = datetime.utcnow().isoformat() + "Z"
+    started = time.perf_counter()
+
+    try:
+        response = httpx.post(
+            f"{SCAN_AI_BASE_URL}/chat/completions",
+            json=request_json,
+            headers={
+                "Authorization": f"Bearer {api_key}",
+                "Content-Type": "application/json",
+            },
+            timeout=min(SCAN_CITY_AI_TIMEOUT_SEC, 15),
+        )
+        response.raise_for_status()
+        result = response.json()
+        content = ((result.get("choices") or [{}])[0].get("message") or {}).get("content") or "{}"
+        parsed = json.loads(content) if isinstance(content, str) else content
+        if not isinstance(parsed, dict):
+            raise ValueError("AI returned non-dict overview")
+
+        payload: Dict[str, Any] = {
+            "overview_zh": str(parsed.get("overview_zh") or parsed.get("overview_en") or ""),
+            "overview_en": str(parsed.get("overview_en") or parsed.get("overview_zh") or ""),
+            "highlights": [
+                {
+                    "city": str(h.get("city", "")),
+                    "note_zh": str(h.get("note_zh", "")),
+                    "note_en": str(h.get("note_en", "")),
+                }
+                for h in (parsed.get("highlights") if isinstance(parsed.get("highlights"), list) else [])
+                if isinstance(h, dict)
+            ][:5],
+            "generated_at": generated_at,
+        }
+    except Exception as exc:
+        logger.warning("Market overview AI failed: {}", exc)
+        payload = {
+            "overview_zh": "市场概览暂时无法生成，请稍后刷新。",
+            "overview_en": "Market overview temporarily unavailable, please refresh later.",
+            "highlights": [],
+            "generated_at": generated_at,
+        }
+
+    duration_ms = int((time.perf_counter() - started) * 1000)
+    logger.info(
+        "market_overview cities={} locale={} duration_ms={} cached={}",
+        len(rows),
+        locale,
+        duration_ms,
+        False,
+    )
+
+    entry = {"expires_at": time.time() + _OVERVIEW_CACHE_TTL_SEC, "payload": payload}
+    with _OVERVIEW_CACHE_LOCK:
+        _OVERVIEW_CACHE[key] = entry
+
+    return payload