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

2026-04-26 14:03:13 +08:00
parent f9ad34d7c0
commit ef8ef833b9
7 changed files with 614 additions and 36 deletions
@@ -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",
+        },
+    )
@@ -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_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."
+    reasoning_zh = str(partial_ai.get("reasoning_zh") or "").strip() or (
+        "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,
    *,