Sync dynamic commentary across bot and dashboard
This commit is contained in:
2569718930@qq.com
@@ -89,3 +89,21 @@
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{"city": "test_city", "timestamp": "2026-03-04 16:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
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{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.85, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.5, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 29.5, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "shadow_prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.85, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 14:30", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 10:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.5625, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 26.0, "peak_status": "before", "prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "shadow_prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.5625}
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{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
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{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 33.3, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 33.0, "peak_status": "in_window", "prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "shadow_prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 33.3, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
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{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 22:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
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{"city": "test_city", "timestamp": "2026-03-04 16:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
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{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.85, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.5, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 29.5, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "shadow_prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.85, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 14:30", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 10:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.5625, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 26.0, "peak_status": "before", "prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "shadow_prob_snapshot": [{"v": 30, "p": 0.254}, {"v": 29, "p": 0.234}, {"v": 31, "p": 0.185}, {"v": 28, "p": 0.146}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.5625}
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{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
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{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 33.3, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 33.0, "peak_status": "in_window", "prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "shadow_prob_snapshot": [{"v": 33, "p": 0.456}, {"v": 34, "p": 0.391}, {"v": 35, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 33.3, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 17:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
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{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 22:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
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{"city": "test_city", "timestamp": "2026-03-04 16:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 23.0, "raw_sigma": 0.46875, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 23.0, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "shadow_prob_snapshot": [{"v": 23, "p": 0.834}, {"v": 24, "p": 0.166}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 23.0, "calibrated_sigma": 0.46875}
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{"city": "test_city", "timestamp": "2026-03-04 14:00", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.85, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.5, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 29.5, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "shadow_prob_snapshot": [{"v": 30, "p": 0.565}, {"v": 31, "p": 0.341}, {"v": 32, "p": 0.094}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.85, "calibrated_sigma": 1.09375}
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{"city": "test_city", "timestamp": "2026-03-04 14:30", "date": "2026-03-04", "temp_symbol": "°C", "raw_mu": 29.7, "raw_sigma": 1.09375, "deb_prediction": null, "ensemble": {"p10": 27.0, "median": 29.0, "p90": 31.0}, "multi_model": {"Open-Meteo": 30.0}, "max_so_far": 28.0, "peak_status": "in_window", "prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "shadow_prob_snapshot": [{"v": 30, "p": 0.35}, {"v": 29, "p": 0.299}, {"v": 31, "p": 0.187}, {"v": 28, "p": 0.117}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260320132525", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 29.7, "calibrated_sigma": 1.09375}
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@@ -870,9 +870,9 @@ export function FutureForecastModal() {
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}}
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/>
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</div>
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<div className="future-front-meta">
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<span className="future-front-pill">
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{t("future.judgement")}: {view.front.label}
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<div className="future-front-meta">
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<span className="future-front-pill">
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{t("future.judgement")}: {view.front.label}
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</span>
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<span className="future-front-pill">
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{t("future.confidence")}:{" "}
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@@ -883,6 +883,11 @@ export function FutureForecastModal() {
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{Math.round(view.front.precipMax)}%
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</span>
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</div>
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{view.front.summary ? (
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<div className="future-trend-summary">
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{view.front.summary}
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</div>
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) : null}
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</div>
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<div className="future-trend-grid">
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{view.front.metrics.slice(0, 6).map((metric) => (
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@@ -293,6 +293,10 @@ export interface CityDetail {
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}>;
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trend?: TrendInfo;
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peak?: PeakInfo;
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dynamic_commentary?: {
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summary?: string | null;
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notes?: string[] | null;
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};
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ai_analysis?: string | AiAnalysisStructured | null;
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updated_at?: string;
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multi_model_daily?: Record<string, DailyModelForecast>;
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+263
-67
@@ -528,6 +528,15 @@ export function computeFrontTrendSignal(
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dateStr: string,
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locale: Locale = "zh-CN",
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) {
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const backendSummary =
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dateStr === detail.local_date
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? String(detail.dynamic_commentary?.summary || "").trim()
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: "";
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const backendNotes = Array.isArray(detail.dynamic_commentary?.notes)
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? detail.dynamic_commentary?.notes
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?.map((item) => String(item || "").trim())
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.filter(Boolean) || []
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: [];
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const slice = getFutureSlice(detail, dateStr);
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const currentTemp = Number(detail.current?.temp);
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const currentDew = Number(detail.current?.dewpoint);
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@@ -544,9 +553,11 @@ export function computeFrontTrendSignal(
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}>,
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precipMax: 0,
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score: 0,
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summary: isEnglish(locale)
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? "Insufficient intraday structured data. Keep baseline monitoring."
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: "当日日内结构化数据不足，暂时只保留基础监控。",
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summary:
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backendSummary ||
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(isEnglish(locale)
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? "Insufficient intraday structured data. Keep baseline monitoring."
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: "当日日内结构化数据不足，暂时只保留基础监控。"),
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weatherGovPeriods: [] as ReturnType<typeof getForecastTextForDate>,
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};
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}
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@@ -722,76 +733,261 @@ export function computeFrontTrendSignal(
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const label = score >= 18 ? warmLabel : score <= -18 ? coldLabel : monitorLabel;
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const confidence =
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Math.abs(score) >= 45 ? "high" : Math.abs(score) >= 22 ? "medium" : "low";
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const summary = (() => {
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const parts: string[] = [];
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if (isEnglish(locale)) {
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if (lastBucket === "southerly" && firstBucket !== "southerly") {
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parts.push("Low-level wind turns more southerly.");
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} else if (lastBucket === "northerly" && firstBucket !== "northerly") {
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parts.push("Low-level wind shifts toward a northerly regime.");
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}
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if (tempDelta >= 0.8) {
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parts.push(`Temperature rises by ${formatDelta(tempDelta, detail.temp_symbol)}.`);
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} else if (tempDelta <= -0.8) {
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parts.push(`Temperature eases by ${formatDelta(tempDelta, detail.temp_symbol)}.`);
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}
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if (dewDelta >= 0.8) {
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parts.push("Dew point is lifting, suggesting moisture transport is strengthening.");
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} else if (dewDelta <= -0.8) {
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parts.push("Dew point is falling, so low-level air is turning drier.");
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}
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if (cloudDelta >= 15) {
|
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parts.push("Cloud cover is building.");
|
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} else if (cloudDelta <= -15) {
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parts.push("Cloud cover is easing.");
|
||||
}
|
||||
|
||||
if (pressureDelta >= 1) {
|
||||
parts.push("Pressure rebound argues for a cooler push.");
|
||||
} else if (pressureDelta <= -1) {
|
||||
parts.push("Pressure is softening, which is less hostile to warming.");
|
||||
}
|
||||
|
||||
if (precipMax >= 50) {
|
||||
parts.push("Precipitation risk is high enough to watch for cloud/rain suppression.");
|
||||
}
|
||||
|
||||
if (!parts.length) {
|
||||
parts.push(`Structured trend is mixed, so the core judgement still centers on ${windowText}.`);
|
||||
} else {
|
||||
parts.push(`Core judgement remains focused on ${windowText}.`);
|
||||
}
|
||||
} else {
|
||||
if (lastBucket === "southerly" && firstBucket !== "southerly") {
|
||||
parts.push("低层风向更偏南，暖空气输送权重上升。");
|
||||
} else if (lastBucket === "northerly" && firstBucket !== "northerly") {
|
||||
parts.push("低层风向转偏北，冷空气影响权重上升。");
|
||||
}
|
||||
|
||||
if (tempDelta >= 0.8) {
|
||||
parts.push(`气温抬升 ${formatDelta(tempDelta, detail.temp_symbol)}。`);
|
||||
} else if (tempDelta <= -0.8) {
|
||||
parts.push(`气温回落 ${formatDelta(tempDelta, detail.temp_symbol)}。`);
|
||||
}
|
||||
|
||||
if (dewDelta >= 0.8) {
|
||||
parts.push("露点同步上升，说明暖湿输送在增强。");
|
||||
} else if (dewDelta <= -0.8) {
|
||||
parts.push("露点回落，低层空气在转干。");
|
||||
}
|
||||
|
||||
if (cloudDelta >= 15) {
|
||||
parts.push("云量正在增多。");
|
||||
} else if (cloudDelta <= -15) {
|
||||
parts.push("云量正在回落。");
|
||||
}
|
||||
|
||||
if (pressureDelta >= 1) {
|
||||
parts.push("气压回升，更偏向冷空气压入。");
|
||||
} else if (pressureDelta <= -1) {
|
||||
parts.push("气压走低，对增温压制减弱。");
|
||||
}
|
||||
|
||||
if (precipMax >= 50) {
|
||||
parts.push("降水概率已足以关注云雨压温。");
|
||||
}
|
||||
|
||||
if (!parts.length) {
|
||||
parts.push(`结构信号分化较大，核心仍围绕${windowText}观察。`);
|
||||
} else {
|
||||
parts.push(`核心判断窗口仍以${windowText}为主。`);
|
||||
}
|
||||
}
|
||||
|
||||
return parts.join(isEnglish(locale) ? " " : "");
|
||||
})();
|
||||
const cloudNote = (() => {
|
||||
if (cloudDelta >= 15 && tempDelta >= 0.8 && dewDelta >= 0.8) {
|
||||
return isEnglish(locale)
|
||||
? "Clouds are increasing while temperature and dew point still rise; this usually fits ongoing warm-moist transport rather than immediate cooling."
|
||||
: "云量上升时温度和露点仍在抬升，更像暖湿输送持续中，而不是立刻转凉。";
|
||||
}
|
||||
if (cloudDelta >= 15 && tempDelta >= 0 && lastBucket === "southerly") {
|
||||
return isEnglish(locale)
|
||||
? "Clouds are building without clear cooling, and the low-level wind still leans southerly; watch for warm advection to continue."
|
||||
: "云量增多但未明显降温，且低层风仍偏南，需继续关注暖平流是否延续。";
|
||||
}
|
||||
if (cloudDelta >= 15 && tempDelta < 0 && precipMax >= 40) {
|
||||
return isEnglish(locale)
|
||||
? "Clouds are thickening while temperature eases and precipitation risk is elevated; cloud/rain suppression is becoming more likely."
|
||||
: "云量增厚且气温回落，同时降水概率偏高，更像云雨压温开始生效。";
|
||||
}
|
||||
if (cloudDelta >= 15 && tempDelta < 0 && pressureDelta >= 1) {
|
||||
return isEnglish(locale)
|
||||
? "Clouds are increasing while temperature softens and pressure rebounds; watch for cold-air push or frontal suppression."
|
||||
: "云量上升同时气温走弱、气压回升，需留意冷空气压入或锋面压温。";
|
||||
}
|
||||
if (cloudDelta <= -15 && tempDelta >= 0.8) {
|
||||
return isEnglish(locale)
|
||||
? "Cloud cover is easing while temperature rises; daytime heating efficiency is improving."
|
||||
: "云量回落且温度抬升，白天增温效率在改善。";
|
||||
}
|
||||
return isEnglish(locale)
|
||||
? "Read cloud-cover change together with temperature, dew point, wind, and precipitation; cloud change alone does not define the regime."
|
||||
: "云量变化需要结合温度、露点、风向和降水一起看，不能单独决定天气形势。";
|
||||
})();
|
||||
const dewNote = (() => {
|
||||
if (dewDelta >= 1.2 && tempDelta >= 0.8) {
|
||||
return isEnglish(locale)
|
||||
? "Dew point and temperature rise together, which usually supports strengthening warm-moist transport."
|
||||
: "露点和温度同步抬升，更偏向暖湿输送增强。";
|
||||
}
|
||||
if (dewDelta >= 1.2 && precipMax >= 40) {
|
||||
return isEnglish(locale)
|
||||
? "Moisture is building while precipitation risk is already notable; watch for showers to cap daytime heating."
|
||||
: "水汽在累积且降水风险已抬升，需关注阵雨对午后增温的压制。";
|
||||
}
|
||||
if (dewDelta <= -1.2 && tempDelta <= 0) {
|
||||
return isEnglish(locale)
|
||||
? "Drier low-level air is arriving together with softer temperature, which leans away from warm-moist support."
|
||||
: "低层空气在转干且温度偏弱，暖湿支撑正在减弱。";
|
||||
}
|
||||
return isEnglish(locale)
|
||||
? "Use dew-point change to judge whether low-level warm-moist transport is strengthening or fading."
|
||||
: "露点变化主要用于判断低层暖湿输送是在增强还是减弱。";
|
||||
})();
|
||||
const pressureNote = (() => {
|
||||
if (pressureDelta >= 1.2 && tempDelta <= -0.8) {
|
||||
return isEnglish(locale)
|
||||
? "Pressure rebound with cooling usually points to a cooler push or frontal suppression."
|
||||
: "气压回升且温度走弱，更像冷空气压入或锋面压温。";
|
||||
}
|
||||
if (pressureDelta <= -1.0 && tempDelta >= 0.8) {
|
||||
return isEnglish(locale)
|
||||
? "Pressure is softening while temperature rises, a setup less hostile to warming."
|
||||
: "气压走低同时温度抬升，对增温的压制相对减弱。";
|
||||
}
|
||||
return isEnglish(locale)
|
||||
? "Pressure change is used as a supporting signal for cold-air push versus warming resilience."
|
||||
: "气压变化更适合作为冷空气压入或增温韧性的辅助判断。";
|
||||
})();
|
||||
const windNote = (() => {
|
||||
if (firstBucket !== lastBucket && lastBucket === "southerly") {
|
||||
return isEnglish(locale)
|
||||
? "Wind turns toward a southerly regime, which is more favorable for warming."
|
||||
: "风向转偏南，更有利于增温。";
|
||||
}
|
||||
if (firstBucket !== lastBucket && lastBucket === "northerly") {
|
||||
return isEnglish(locale)
|
||||
? "Wind turns toward a northerly regime, which is more favorable for cooling."
|
||||
: "风向转偏北，更有利于降温。";
|
||||
}
|
||||
if (lastBucket === "southerly") {
|
||||
return isEnglish(locale)
|
||||
? "Low-level flow remains southerly, so warm advection has not been disrupted."
|
||||
: "低层风维持偏南，暖平流支撑尚未被破坏。";
|
||||
}
|
||||
if (lastBucket === "northerly") {
|
||||
return isEnglish(locale)
|
||||
? "Low-level flow remains northerly, so cooling-side support is still present."
|
||||
: "低层风维持偏北，降温侧支撑仍在。";
|
||||
}
|
||||
return isEnglish(locale)
|
||||
? "Wind-direction change matters most when it crosses into southerly or northerly buckets."
|
||||
: "风向变化最关键的是是否跨入偏南或偏北风桶。";
|
||||
})();
|
||||
const precipNote = (() => {
|
||||
if (precipMax >= 60) {
|
||||
return isEnglish(locale)
|
||||
? "Precipitation risk is high enough that cloud/rain suppression can materially change the peak outcome."
|
||||
: "降水概率已高到足以显著改变峰值兑现结果，需要重点防压温。";
|
||||
}
|
||||
if (precipMax >= 40) {
|
||||
return isEnglish(locale)
|
||||
? "Precipitation risk is meaningful; watch whether cloud and showers interrupt daytime heating."
|
||||
: "降水概率已有存在感，需要关注云系和阵雨是否打断白天增温。";
|
||||
}
|
||||
return isEnglish(locale)
|
||||
? "Precipitation risk remains limited and is used mainly as a suppression check."
|
||||
: "降水风险暂时有限，主要作为压温风险校验项。";
|
||||
})();
|
||||
|
||||
const metrics = [
|
||||
{
|
||||
label: isEnglish(locale) ? "Temperature delta" : "温度变化",
|
||||
note: isEnglish(locale)
|
||||
? `Official Open-Meteo hourly data; window: ${windowText}`
|
||||
: `官方 Open-Meteo 小时数据；计算窗口：${windowText}`,
|
||||
tone: tempDelta >= 0.8 ? "warm" : tempDelta <= -0.8 ? "cold" : "",
|
||||
value: formatDelta(tempDelta, detail.temp_symbol),
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Dew point delta" : "露点变化",
|
||||
note: dewNote,
|
||||
tone: dewDelta >= 0.8 ? "warm" : dewDelta <= -0.8 ? "cold" : "",
|
||||
value: formatDelta(dewDelta, detail.temp_symbol),
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Pressure delta" : "气压变化",
|
||||
note: pressureNote,
|
||||
tone: pressureDelta >= 1 ? "cold" : pressureDelta <= -1 ? "warm" : "",
|
||||
value: formatDelta(pressureDelta, " hPa"),
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Wind-direction evolution" : "风向演变",
|
||||
note: windNote,
|
||||
value: `${bucketLabel(firstBucket, locale)} -> ${bucketLabel(lastBucket, locale)}`,
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Precip probability" : "降水概率",
|
||||
note: precipNote,
|
||||
tone: precipMax >= 50 ? "cold" : "",
|
||||
value: `${Math.round(precipMax)}%`,
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Cloud-cover delta" : "云量变化",
|
||||
note: cloudNote,
|
||||
tone:
|
||||
cloudDelta >= 15 && tempDelta >= 0
|
||||
? "warm"
|
||||
: cloudDelta >= 15 && tempDelta < 0
|
||||
? "cold"
|
||||
: "",
|
||||
value: formatDelta(cloudDelta, "%"),
|
||||
},
|
||||
];
|
||||
|
||||
if (backendNotes.length) {
|
||||
backendNotes.slice(0, metrics.length).forEach((note, index) => {
|
||||
if (!note) return;
|
||||
metrics[index] = {
|
||||
...metrics[index],
|
||||
note,
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
return {
|
||||
confidence,
|
||||
label,
|
||||
metrics: [
|
||||
{
|
||||
label: isEnglish(locale) ? "Temperature delta" : "温度变化",
|
||||
note: isEnglish(locale)
|
||||
? `Official Open-Meteo hourly data; window: ${windowText}`
|
||||
: `官方 Open-Meteo 小时数据；计算窗口：${windowText}`,
|
||||
tone: tempDelta >= 0.8 ? "warm" : tempDelta <= -0.8 ? "cold" : "",
|
||||
value: formatDelta(tempDelta, detail.temp_symbol),
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Dew point delta" : "露点变化",
|
||||
note: isEnglish(locale)
|
||||
? "Rising dew point often supports warm/wet advection"
|
||||
: "露点上升更偏向暖湿平流",
|
||||
tone: dewDelta >= 0.8 ? "warm" : dewDelta <= -0.8 ? "cold" : "",
|
||||
value: formatDelta(dewDelta, detail.temp_symbol),
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Pressure delta" : "气压变化",
|
||||
note: isEnglish(locale)
|
||||
? "Pressure rebound usually implies cold-air push"
|
||||
: "气压回升更偏向冷空气压入",
|
||||
tone: pressureDelta >= 1 ? "cold" : pressureDelta <= -1 ? "warm" : "",
|
||||
value: formatDelta(pressureDelta, " hPa"),
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Wind-direction evolution" : "风向演变",
|
||||
note: isEnglish(locale)
|
||||
? "Warming-favor: S/SW; cooling-favor: N/NW"
|
||||
: "增温有利：南/西南风；降温有利：北/西北风",
|
||||
value: `${bucketLabel(firstBucket, locale)} -> ${bucketLabel(lastBucket, locale)}`,
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Precip probability" : "降水概率",
|
||||
note: "weather.gov / Open-Meteo",
|
||||
tone: precipMax >= 50 ? "cold" : "",
|
||||
value: `${Math.round(precipMax)}%`,
|
||||
},
|
||||
{
|
||||
label: isEnglish(locale) ? "Cloud-cover delta" : "云量变化",
|
||||
note: isEnglish(locale)
|
||||
? "Cloud increase without cooling may imply warm advection"
|
||||
: "云量抬升但未降温，常见于暖平流前段",
|
||||
tone:
|
||||
cloudDelta >= 15 && tempDelta >= 0
|
||||
? "warm"
|
||||
: cloudDelta >= 15 && tempDelta < 0
|
||||
? "cold"
|
||||
: "",
|
||||
value: formatDelta(cloudDelta, "%"),
|
||||
},
|
||||
],
|
||||
metrics,
|
||||
precipMax,
|
||||
score,
|
||||
summary:
|
||||
label === warmLabel
|
||||
? isEnglish(locale)
|
||||
? `Southerly flow strengthens with rising dew point and temperature. ${windowText} leans warm advection.`
|
||||
: `风向更偏南 / 西南，露点与温度整体抬升，${windowText}偏向暖平流。`
|
||||
: label === coldLabel
|
||||
? isEnglish(locale)
|
||||
? `Temperature declines with pressure rebound and/or northerly shift. ${windowText} leans cold-front suppression.`
|
||||
: `温度下滑、气压回升或风向转北，${windowText}更像冷锋或冷平流压制。`
|
||||
: isEnglish(locale)
|
||||
? `Structured trend uses weather.gov + Open-Meteo, with core judgement focused on ${windowText}.`
|
||||
: `结构化来源以 weather.gov 和 Open-Meteo 为主，核心判断窗口为${windowText}。`,
|
||||
summary: backendSummary || summary,
|
||||
weatherGovPeriods,
|
||||
};
|
||||
}
|
||||
|
||||
@@ -31,6 +31,14 @@ SETTLEMENT_SOURCE_LABELS = {
|
||||
"mgm": "MGM",
|
||||
}
|
||||
|
||||
_CLOUD_RANK_LABELS = {
|
||||
0: "晴空到少云",
|
||||
1: "少云",
|
||||
2: "散云",
|
||||
3: "多云",
|
||||
4: "阴天",
|
||||
}
|
||||
|
||||
|
||||
def _sf(v):
|
||||
"""Safe float conversion — prevents JSON str types from breaking math."""
|
||||
@@ -53,6 +61,107 @@ def _resolve_settlement_source_label(city_name: Optional[str]) -> str:
|
||||
return SETTLEMENT_SOURCE_LABELS.get(source, source.upper())
|
||||
|
||||
|
||||
def _wind_bucket_label(wdir: Optional[float]) -> str:
|
||||
if wdir is None:
|
||||
return "风向信号不明确"
|
||||
deg = float(wdir) % 360
|
||||
if 135 <= deg < 225:
|
||||
return "南风主导"
|
||||
if 45 <= deg < 135:
|
||||
return "东风主导"
|
||||
if 225 <= deg < 315:
|
||||
return "西风主导"
|
||||
return "北风主导"
|
||||
|
||||
|
||||
def _describe_recent_structure(
|
||||
recent_obs: List[Dict[str, Any]],
|
||||
peak_status: str,
|
||||
trend_direction: str,
|
||||
cur_temp: Optional[float],
|
||||
max_so_far: Optional[float],
|
||||
temp_symbol: str,
|
||||
primary_current: Dict[str, Any],
|
||||
) -> Tuple[str, List[str]]:
|
||||
if len(recent_obs) < 2:
|
||||
return "", []
|
||||
|
||||
oldest = recent_obs[-1]
|
||||
newest = recent_obs[0]
|
||||
|
||||
temp_old = _sf(oldest.get("temp"))
|
||||
temp_new = _sf(newest.get("temp"))
|
||||
wdir_old = _sf(oldest.get("wdir"))
|
||||
wdir_new = _sf(newest.get("wdir"))
|
||||
altim_old = _sf(oldest.get("altim"))
|
||||
altim_new = _sf(newest.get("altim"))
|
||||
cloud_old = int(oldest.get("cloud_rank") or 0)
|
||||
cloud_new = int(newest.get("cloud_rank") or 0)
|
||||
humidity = _sf(primary_current.get("humidity"))
|
||||
wx_desc = str(primary_current.get("wx_desc") or "").strip()
|
||||
|
||||
temp_delta = None
|
||||
if temp_old is not None and temp_new is not None:
|
||||
temp_delta = temp_new - temp_old
|
||||
|
||||
wind_angle = None
|
||||
if wdir_old is not None and wdir_new is not None:
|
||||
wind_angle = abs(wdir_new - wdir_old)
|
||||
if wind_angle > 180:
|
||||
wind_angle = 360 - wind_angle
|
||||
|
||||
altim_delta = None
|
||||
if altim_old is not None and altim_new is not None:
|
||||
altim_delta = altim_new - altim_old
|
||||
|
||||
cloud_delta = cloud_new - cloud_old
|
||||
lines: List[str] = []
|
||||
|
||||
if cloud_delta >= 2 and temp_delta is not None and temp_delta >= 0:
|
||||
lines.append("云层明显增厚，但近报尚未跟随降温，短时更像中高云增多或暖湿输送前段。")
|
||||
elif cloud_delta >= 2 and temp_delta is not None and temp_delta <= -0.5:
|
||||
lines.append("云量抬升且温度同步回落，云雨压温的约束正在增强。")
|
||||
elif cloud_delta <= -2 and temp_delta is not None and temp_delta >= 0.5:
|
||||
lines.append("云量回落并伴随升温，短时日照增温效率在改善。")
|
||||
|
||||
if wind_angle is not None and wind_angle >= 60:
|
||||
lines.append(
|
||||
f"低层风向出现明显切换，由 {_wind_bucket_label(wdir_old)} 转为 {_wind_bucket_label(wdir_new)}。"
|
||||
)
|
||||
elif wdir_new is not None:
|
||||
lines.append(f"当前低层风场以{_wind_bucket_label(wdir_new)}为主。")
|
||||
|
||||
if altim_delta is not None:
|
||||
if altim_delta <= -1.5 and trend_direction != "falling":
|
||||
lines.append("气压继续走低，边界层仍偏活跃，峰值尚不能轻判结束。")
|
||||
elif altim_delta >= 1.5 and peak_status != "before":
|
||||
lines.append("气压回升信号更明显，若后续再配合回落，日高温锁定概率会继续上升。")
|
||||
|
||||
if humidity is not None and humidity >= 80 and not wx_desc:
|
||||
lines.append(f"湿度已到 {humidity:.0f}% 左右，后续若云层继续增厚，需要防范压温。")
|
||||
elif wx_desc:
|
||||
lines.append(f"当前伴随“{wx_desc}”天气现象，短时体感与实测升温效率通常都会受抑制。")
|
||||
|
||||
if max_so_far is not None and cur_temp is not None:
|
||||
gap = max_so_far - cur_temp
|
||||
if gap >= 2.0 and peak_status != "before":
|
||||
lines.append(
|
||||
f"当前温度较今日峰值已回落 {gap:.1f}{temp_symbol}，若后续再无明显回补，日高温大概率已接近锁定。"
|
||||
)
|
||||
elif gap <= 0.5 and peak_status == "in_window":
|
||||
lines.append("当前温度仍贴近当日峰值，窗口内仍保留再创新高的可能。")
|
||||
|
||||
if not lines:
|
||||
if trend_direction == "rising":
|
||||
lines.append("近报仍偏升温，短时还看不到明确见顶信号。")
|
||||
elif trend_direction == "falling":
|
||||
lines.append("近报已进入回落段，后续重点看回落是否延续。")
|
||||
else:
|
||||
lines.append("当前结构信号偏中性，仍需继续盯近报温度与风云演变。")
|
||||
|
||||
return lines[0], lines
|
||||
|
||||
|
||||
def analyze_weather_trend(
|
||||
weather_data: dict,
|
||||
temp_symbol: str,
|
||||
@@ -329,6 +438,21 @@ def analyze_weather_trend(
|
||||
"暂不能单凭回落判定今日高温已锁定。"
|
||||
)
|
||||
|
||||
recent_obs = metar.get("recent_obs", [])
|
||||
dynamic_summary, dynamic_notes = _describe_recent_structure(
|
||||
recent_obs=recent_obs,
|
||||
peak_status=peak_status,
|
||||
trend_direction=trend_direction,
|
||||
cur_temp=cur_temp,
|
||||
max_so_far=max_so_far,
|
||||
temp_symbol=temp_symbol,
|
||||
primary_current=primary_current,
|
||||
)
|
||||
if dynamic_summary:
|
||||
insights.append(f"🧩 <b>结构解读</b>：{dynamic_summary}")
|
||||
for note in dynamic_notes:
|
||||
ai_features.append(f"🧩 结构解读: {note}")
|
||||
|
||||
# === Ensemble ===
|
||||
ensemble = weather_data.get("ensemble", {})
|
||||
ens_p10 = _sf(ensemble.get("p10"))
|
||||
@@ -379,7 +503,6 @@ def analyze_weather_trend(
|
||||
|
||||
# Shock Score
|
||||
shock_score = 0.0
|
||||
recent_obs = metar.get("recent_obs", [])
|
||||
if len(recent_obs) >= 2:
|
||||
oldest = recent_obs[-1]
|
||||
newest = recent_obs[0]
|
||||
@@ -788,6 +911,10 @@ def analyze_weather_trend(
|
||||
"max_so_far": max_so_far,
|
||||
"cur_temp": cur_temp,
|
||||
"wu_settle": apply_city_settlement(city_name, max_so_far) if max_so_far is not None else None,
|
||||
"dynamic_commentary": {
|
||||
"summary": dynamic_summary,
|
||||
"notes": dynamic_notes,
|
||||
},
|
||||
}
|
||||
display_str = "\n".join(insights) if insights else ""
|
||||
return display_str, "\n".join(ai_features), structured
|
||||
|
||||
@@ -258,3 +258,50 @@ class TestTrendDirection:
|
||||
)
|
||||
_, _, sd = analyze_weather_trend(data, "°C", "test_city")
|
||||
assert sd["trend_info"]["direction"] == "stagnant"
|
||||
|
||||
|
||||
class TestDynamicCommentary:
|
||||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||||
@patch("src.analysis.trend_engine.append_probability_snapshot")
|
||||
@patch("src.analysis.trend_engine.update_daily_record")
|
||||
def test_dynamic_commentary_detects_cloud_build_without_cooling(
|
||||
self, _udr, _snapshot, _deb_acc, _dw
|
||||
):
|
||||
data = _make_weather_data(
|
||||
cur_temp=28.0,
|
||||
max_so_far=28.2,
|
||||
local_time="2026-03-04 14:00",
|
||||
recent_temps=[("14:00", 28.0), ("13:00", 27.6), ("12:00", 27.0)],
|
||||
recent_obs=[
|
||||
{"temp": 28.0, "wdir": 185, "wspd": 8, "cloud_rank": 3, "altim": 1009.2},
|
||||
{"temp": 27.6, "wdir": 170, "wspd": 7, "cloud_rank": 2, "altim": 1010.0},
|
||||
{"temp": 27.2, "wdir": 155, "wspd": 6, "cloud_rank": 1, "altim": 1010.8},
|
||||
],
|
||||
)
|
||||
|
||||
display_str, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
|
||||
|
||||
summary = sd["dynamic_commentary"]["summary"]
|
||||
notes = sd["dynamic_commentary"]["notes"]
|
||||
assert summary
|
||||
assert "云层明显增厚" in summary
|
||||
assert "结构解读" in display_str
|
||||
assert any("云层明显增厚" in note for note in notes)
|
||||
assert "结构解读" in ai_context
|
||||
|
||||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||||
@patch("src.analysis.trend_engine.append_probability_snapshot")
|
||||
@patch("src.analysis.trend_engine.update_daily_record")
|
||||
def test_dynamic_commentary_falls_back_when_recent_obs_missing(
|
||||
self, _udr, _snapshot, _deb_acc, _dw
|
||||
):
|
||||
data = _make_weather_data(recent_obs=[])
|
||||
|
||||
display_str, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
|
||||
|
||||
assert sd["dynamic_commentary"]["summary"] == ""
|
||||
assert sd["dynamic_commentary"]["notes"] == []
|
||||
assert "结构解读" not in display_str
|
||||
assert "结构解读" not in ai_context
|
||||
|
||||
@@ -350,6 +350,7 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
|
||||
probability_calibrated_mu = None
|
||||
probability_calibrated_sigma = None
|
||||
ai_text = ""
|
||||
dynamic_commentary = {"summary": "", "notes": []}
|
||||
try:
|
||||
_, _ai_context, sd = _trend_analyze(raw, sym, city)
|
||||
|
||||
@@ -364,6 +365,7 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
|
||||
probability_raw_sigma = sd.get("probability_raw_sigma")
|
||||
probability_calibrated_mu = sd.get("probability_calibrated_mu")
|
||||
probability_calibrated_sigma = sd.get("probability_calibrated_sigma")
|
||||
dynamic_commentary = sd.get("dynamic_commentary") or dynamic_commentary
|
||||
trend_info["is_dead_market"] = sd.get("trend_info", {}).get("is_dead_market", False)
|
||||
trend_info["direction"] = sd.get("trend_info", {}).get("direction", trend_info.get("direction", "unknown"))
|
||||
trend_info["is_cooling"] = sd.get("trend_info", {}).get("is_cooling", False)
|
||||
@@ -666,6 +668,7 @@ def _analyze(city: str, force_refresh: bool = False) -> Dict[str, Any]:
|
||||
"last_h": last_peak_h,
|
||||
"status": peak_status,
|
||||
},
|
||||
"dynamic_commentary": dynamic_commentary,
|
||||
"hourly": today_hourly,
|
||||
"hourly_next_48h": next_48h_hourly,
|
||||
"metar_today_obs": metar_today_obs_payload,
|
||||
@@ -850,6 +853,7 @@ def _build_city_detail_payload(
|
||||
if not _is_excluded_model_name(k)
|
||||
},
|
||||
"probabilities": data.get("probabilities") or {"mu": None, "distribution": []},
|
||||
"dynamic_commentary": data.get("dynamic_commentary") or {"summary": "", "notes": []},
|
||||
"market_scan": market_scan,
|
||||
"risk": data.get("risk"),
|
||||
"ai_analysis": data.get("ai_analysis") or "",
|
||||
|
||||
Reference in New Issue
Block a user