UPDATE

rag/services/irrigation.py

@@ -11,7 +11,10 @@ from django.db import transaction
 
 from farm_data.models import SensorData
 from farm_data.services import (
+    build_ai_farm_snapshot,
     clone_snapshot_as_runtime_plant,
+    get_ai_snapshot_metric,
+    get_ai_snapshot_weather,
     get_farm_plant_snapshot_by_name,
 )
 from irrigation.evapotranspiration import (
@@ -55,13 +58,15 @@ def _safe_float(value: Any, default: float = 0.0) -> float:
         return default
 
 
-def _sensor_metric(sensor: SensorData | None, metric: str) -> float | None:
-    if sensor is None or not isinstance(sensor.sensor_payload, dict):
-        return None
-    for payload in sensor.sensor_payload.values():
-        if isinstance(payload, dict) and payload.get(metric) is not None:
-            return _safe_float(payload.get(metric), default=0.0)
-    return None
+def _aggregated_metric(ai_snapshot: dict[str, Any] | None, metric: str) -> float | None:
+    value = get_ai_snapshot_metric(ai_snapshot, metric)
+    return _safe_float(value, default=0.0) if value is not None else None
+
+
+
+def _aggregated_metric_fallback(ai_snapshot: dict[str, Any] | None, metric: str) -> float | None:
+    """Limited fallback for missing aggregated metrics only; raw payload is intentionally not consulted."""
+    return _aggregated_metric(ai_snapshot, metric)
 
 
 def _coerce_list(value: Any) -> list[Any]:
@@ -275,9 +280,9 @@ def _build_irrigation_ui_payload(
     crop_profile: dict[str, Any],
     active_kc: float,
     irrigation_method: IrrigationMethod | None,
-    sensor: SensorData | None,
+    ai_snapshot: dict[str, Any] | None,
 ) -> dict[str, Any]:
-    soil_moisture = _sensor_metric(sensor, "soil_moisture")
+    soil_moisture = _aggregated_metric_fallback(ai_snapshot, "soil_moisture")
     plan = _normalize_plan(
         llm_result,
         optimizer_result,
@@ -380,6 +385,7 @@ def get_irrigation_recommendation(
         .filter(farm_uuid=resolved_farm_uuid)
         .first()
     )
+    ai_snapshot = build_ai_farm_snapshot(resolved_farm_uuid)
     irrigation_method = _resolve_irrigation_method(sensor, irrigation_method_name)
     _persist_irrigation_method_on_farm(sensor, irrigation_method)
 
@@ -423,6 +429,7 @@ def get_irrigation_recommendation(
         if plant is not None and forecasts:
             optimized_result = _get_optimizer().optimize_irrigation(
                 sensor=sensor,
+                ai_snapshot=ai_snapshot,
                 plant=plant,
                 forecasts=forecasts,
                 daily_water_needs=daily_water_needs,
@@ -518,7 +525,7 @@ def get_irrigation_recommendation(
         crop_profile,
         active_kc,
         irrigation_method,
-        sensor,
+        ai_snapshot,
     )
     result["raw_response"] = raw
     result["simulation_optimizer"] = optimized_result