feat: Add city weather query service with city resolution, forecast processing, and weather summary generation.

src/analysis/city_query_service.py

@@ -103,7 +103,8 @@ def _derive_mgm_daily_highs_from_hourly(
     if not isinstance(hourly, list) or not hourly:
         return {}
 
-    daily_highs: Dict[str, float] = {}
+    samples: List[Tuple[str, float]] = []
+    parsed_datetimes: List[datetime] = []
     local_tz = timezone(timedelta(seconds=int(fallback_utc_offset)))
     for row in hourly:
         if not isinstance(row, dict):
@@ -119,6 +120,9 @@ def _derive_mgm_daily_highs_from_hourly(
                 dt = datetime.fromisoformat(raw_time.replace("Z", "+00:00"))
                 if dt.tzinfo is not None:
                     dt = dt.astimezone(local_tz)
+                else:
+                    dt = dt.replace(tzinfo=local_tz)
+                parsed_datetimes.append(dt)
                 date_key = dt.strftime("%Y-%m-%d")
             except Exception:
                 if len(raw_time) >= 10 and raw_time[4] == "-" and raw_time[7] == "-":
@@ -129,6 +133,24 @@ def _derive_mgm_daily_highs_from_hourly(
         if not date_key:
             continue
 
+        samples.append((date_key, temp))
+
+    if not samples:
+        return {}
+
+    # Guardrail: do not derive "daily highs" from short intraday snippets.
+    if parsed_datetimes:
+        parsed_datetimes.sort()
+        horizon_hours = (
+            parsed_datetimes[-1] - parsed_datetimes[0]
+        ).total_seconds() / 3600.0
+        if horizon_hours < 30:
+            return {}
+    elif len(samples) < 24:
+        return {}
+
+    daily_highs: Dict[str, float] = {}
+    for date_key, temp in samples:
         prev = daily_highs.get(date_key)
         daily_highs[date_key] = temp if prev is None else max(prev, temp)
 
@@ -163,7 +185,7 @@ def _append_future_forecast_lines(
             if mgm_value is not None:
                 mgm_display = f"{float(mgm_value):.1f}"
                 future_forecasts.append(
-                    f"{d[5:]}: {t}{temp_symbol} | 🇺🇸 <b>MGM: {mgm_display}{temp_symbol}</b>"
+                    f"{d[5:]}: {t}{temp_symbol} | <b>MGM: {mgm_display}{temp_symbol}</b>"
                 )
             else:
                 future_forecasts.append(f"{d[5:]}: {t}{temp_symbol}")

src/data_collection/weather_sources.py

@@ -768,22 +768,48 @@ class WeatherDataCollector:
 
             # 5. Fallback for daily_forecasts from hourly data
             if not results.get("daily_forecasts") and results.get("hourly"):
-                from collections import defaultdict
+                # Guardrail: avoid treating short intraday snippets as full-day highs.
-                daily_max = defaultdict(list)
+                hourly_rows = results.get("hourly") or []
-                for h in results["hourly"]:
+                parsed_times = []
-                    t = h.get("time", "")
+                for h in hourly_rows:
-                    temp = h.get("temp")
+                    t = str(h.get("time") or "")
-                    if t and temp is not None:
+                    if "T" not in t:
-                        # Extract date from ISO timestamp like "2026-03-05T12:00:00.000Z"
+                        continue
-                        date_str = t[:10]
+                    try:
-                        daily_max[date_str].append(temp)
+                        parsed_times.append(datetime.fromisoformat(t.replace("Z", "+00:00")))
-                if daily_max:
+                    except Exception:
-                    results["daily_forecasts"] = {}
+                        continue
-                    for d, temps in sorted(daily_max.items()):
+
-                        results["daily_forecasts"][d] = max(temps)
+                horizon_hours = 0.0
+                if len(parsed_times) >= 2:
+                    parsed_times.sort()
+                    horizon_hours = (
+                        parsed_times[-1] - parsed_times[0]
+                    ).total_seconds() / 3600.0
+
+                if len(hourly_rows) >= 24 or horizon_hours >= 30:
+                    from collections import defaultdict
+
+                    daily_max = defaultdict(list)
+                    for h in hourly_rows:
+                        t = h.get("time", "")
+                        temp = h.get("temp")
+                        if t and temp is not None:
+                            # Extract date from ISO timestamp like "2026-03-05T12:00:00.000Z"
+                            date_str = t[:10]
+                            daily_max[date_str].append(temp)
+                    if daily_max:
+                        results["daily_forecasts"] = {}
+                        for d, temps in sorted(daily_max.items()):
+                            results["daily_forecasts"][d] = max(temps)
+                        logger.info(
+                            f"📋 MGM daily_forecasts (from hourly fallback): "
+                            f"{dict(results['daily_forecasts'])}"
+                        )
+                else:
                     logger.info(
-                        f"📋 MGM daily_forecasts (from hourly fallback): "
+                        "📋 Skip MGM daily_forecasts hourly fallback: "
-                        f"{dict(results['daily_forecasts'])}"
+                        f"hourly points={len(hourly_rows)}, horizon={horizon_hours:.1f}h"
                     )
 
             return results if "current" in results else None