adding ai summary - default is disabled

app/models/ai_summary.py

@@ -0,0 +1,74 @@
+"""Data models for AI summarization feature."""
+
+from dataclasses import dataclass, field
+from datetime import datetime
+from typing import Any
+
+
+@dataclass
+class ForecastContext:
+    """Forecast data to include in AI summary prompt."""
+
+    start_time: str
+    end_time: str
+    min_temp: float
+    max_temp: float
+    max_wind_speed: float
+    max_wind_gust: float
+    max_precip_prob: float
+    conditions: list[str] = field(default_factory=list)
+
+    def to_prompt_text(self) -> str:
+        """Format forecast context for LLM prompt."""
+        unique_conditions = list(dict.fromkeys(self.conditions))
+        conditions_str = ", ".join(unique_conditions[:5]) if unique_conditions else "N/A"
+
+        return (
+            f"Period: {self.start_time} to {self.end_time}\n"
+            f"Temperature: {self.min_temp:.0f}F - {self.max_temp:.0f}F\n"
+            f"Wind: up to {self.max_wind_speed:.0f} mph, gusts to {self.max_wind_gust:.0f} mph\n"
+            f"Precipitation probability: up to {self.max_precip_prob:.0f}%\n"
+            f"Conditions: {conditions_str}"
+        )
+
+    def to_dict(self) -> dict[str, Any]:
+        """Convert to dictionary for serialization."""
+        return {
+            "start_time": self.start_time,
+            "end_time": self.end_time,
+            "min_temp": self.min_temp,
+            "max_temp": self.max_temp,
+            "max_wind_speed": self.max_wind_speed,
+            "max_wind_gust": self.max_wind_gust,
+            "max_precip_prob": self.max_precip_prob,
+            "conditions": self.conditions,
+        }
+
+
+@dataclass
+class SummaryNotification:
+    """AI-generated weather alert summary notification."""
+
+    title: str
+    message: str
+    location: str
+    alert_count: int
+    has_changes: bool
+    created_at: datetime = field(default_factory=datetime.now)
+
+    @property
+    def tags(self) -> list[str]:
+        """Get notification tags for AI summary."""
+        return ["robot", "weather", "summary"]
+
+    def to_dict(self) -> dict[str, Any]:
+        """Convert to dictionary for serialization."""
+        return {
+            "title": self.title,
+            "message": self.message,
+            "location": self.location,
+            "alert_count": self.alert_count,
+            "has_changes": self.has_changes,
+            "created_at": self.created_at.isoformat(),
+            "tags": self.tags,
+        }

app/models/state.py

@@ -1,8 +1,8 @@
-"""State management models for alert deduplication."""
+"""State management models for alert deduplication and change detection."""
 
 from dataclasses import dataclass, field
 from datetime import datetime
-from typing import Any
+from typing import Any, Optional
 
 
 @dataclass
@@ -41,12 +41,59 @@ class SentAlertRecord:
         )
 
 
+@dataclass
+class AlertSnapshot:
+    """Snapshot of an alert for change detection between runs."""
+
+    alert_type: str
+    extreme_value: float
+    threshold: float
+    start_time: str
+    end_time: str
+    hour_count: int
+    captured_at: datetime = field(default_factory=datetime.now)
+
+    def to_dict(self) -> dict[str, Any]:
+        """Convert to dictionary for JSON serialization."""
+        return {
+            "alert_type": self.alert_type,
+            "extreme_value": self.extreme_value,
+            "threshold": self.threshold,
+            "start_time": self.start_time,
+            "end_time": self.end_time,
+            "hour_count": self.hour_count,
+            "captured_at": self.captured_at.isoformat(),
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "AlertSnapshot":
+        """Create from dictionary.
+
+        Args:
+            data: The serialized snapshot dict.
+
+        Returns:
+            An AlertSnapshot instance.
+        """
+        return cls(
+            alert_type=data["alert_type"],
+            extreme_value=data["extreme_value"],
+            threshold=data["threshold"],
+            start_time=data["start_time"],
+            end_time=data["end_time"],
+            hour_count=data["hour_count"],
+            captured_at=datetime.fromisoformat(data["captured_at"]),
+        )
+
+
 @dataclass
 class AlertState:
-    """State container for tracking sent alerts."""
+    """State container for tracking sent alerts and change detection."""
 
     sent_alerts: dict[str, SentAlertRecord] = field(default_factory=dict)
     last_updated: datetime = field(default_factory=datetime.now)
+    previous_alert_snapshots: dict[str, AlertSnapshot] = field(default_factory=dict)
+    last_ai_summary_sent: Optional[datetime] = None
 
     def is_duplicate(self, dedup_key: str) -> bool:
         """Check if an alert with this dedup key has already been sent.
@@ -106,6 +153,15 @@ class AlertState:
                 key: record.to_dict() for key, record in self.sent_alerts.items()
             },
             "last_updated": self.last_updated.isoformat(),
+            "previous_alert_snapshots": {
+                key: snapshot.to_dict()
+                for key, snapshot in self.previous_alert_snapshots.items()
+            },
+            "last_ai_summary_sent": (
+                self.last_ai_summary_sent.isoformat()
+                if self.last_ai_summary_sent
+                else None
+            ),
         }
 
     @classmethod
@@ -130,4 +186,21 @@ class AlertState:
             else datetime.now()
         )
 
-        return cls(sent_alerts=sent_alerts, last_updated=last_updated)
+        previous_alert_snapshots = {
+            key: AlertSnapshot.from_dict(snapshot_data)
+            for key, snapshot_data in data.get("previous_alert_snapshots", {}).items()
+        }
+
+        last_ai_summary_str = data.get("last_ai_summary_sent")
+        last_ai_summary_sent = (
+            datetime.fromisoformat(last_ai_summary_str)
+            if last_ai_summary_str
+            else None
+        )
+
+        return cls(
+            sent_alerts=sent_alerts,
+            last_updated=last_updated,
+            previous_alert_snapshots=previous_alert_snapshots,
+            last_ai_summary_sent=last_ai_summary_sent,
+        )