feat: add forecast trending endpoint and ForecastTrendPoint model for simulation data

src/aeros_simulation/router.py

@@ -24,6 +24,7 @@ from src.aeros_project.service import get_project
 from temporal.workflow import SimulationWorkflow
 from .schema import (
     AhmMetricInput,
+    ForecastTrendPoint,
     SimulationCalcResult,
     SimulationCalcResultQuery,
     SimulationInput,
@@ -42,6 +43,7 @@ from .service import (
     get_all,
     get_custom_parameters,
     get_default_simulation,
+    get_forecast_trending,
     get_simulation_by_id,
     get_simulation_with_calc_result,
     get_simulation_with_plot_result,
@@ -171,11 +173,10 @@ async def run_yearly_simulation(
     overhaul_duration = 1200
         
 
-    if next_overhaul:
+    if next_overhaul and last_overhaul:
         next_oh_start = date_to_utc(next_overhaul["start_date"])
         next_oh_duration_hours = next_overhaul["duration_oh"] * 24
 
-        
         overhaul_interval = int(
             (next_oh_start - last_oh_dt).total_seconds() // 3600
         )
@@ -523,12 +524,15 @@ async def get_forecast_eaf(
         oh_date_str = oh_record.value_string
 
     try:
-        # Ensure oh_date is naive
         oh_date = datetime.fromisoformat(oh_date_str).replace(tzinfo=None)
-        next_oh_date = datetime.fromisoformat(next_oh.value_string).replace(tzinfo=None)
     except Exception:
         oh_date = datetime(now.year, 1, 1).replace(tzinfo=None)
 
+    try:
+        next_oh_date = datetime.fromisoformat(next_oh.value_string).replace(tzinfo=None)
+    except Exception:
+        next_oh_date = oh_date + timedelta(hours=8760 * 2)  # fallback: 2 years after last OH
+
     oh_interval = hours_between(oh_date, next_oh_date)
     duration = 168 if time_range == "weekly" else 720
     end_date = now + timedelta(hours=duration)
@@ -579,8 +583,29 @@ async def get_forecast_eaf(
         data=str(simulation_id),
         message=forecast_msg
     )
-    
-    
+
+
+@router.get("/forecast/trending", response_model=StandardResponse[List[ForecastTrendPoint]])
+async def get_forecast_trending_endpoint(
+    db_session: DbSession,
+    time_range: str = Query(..., alias="range", regex="^(weekly|monthly)$"),
+    limit: int = Query(12, ge=1, le=52),
+):
+    """
+    Return EAF/EFOR/SOF/EDH trending for the last N completed weekly or monthly
+    forecast simulations, sorted oldest → newest for chart rendering.
+
+    Query params:
+      range  — "weekly" or "monthly"
+      limit  — max data points (default 12, max 52)
+    """
+    results = await get_forecast_trending(
+        db_session=db_session, time_range=time_range, limit=limit
+    )
+    return StandardResponse(
+        data=results,
+        message=f"{time_range.capitalize()} EAF/EFOR trending retrieved ({len(results)} points)",
+    )
 
 
 @router.get("/custom_parameters", response_model=StandardResponse[list])

src/aeros_simulation/schema.py

@@ -130,6 +130,16 @@ class YearlySimulationInput(DefultBase):
     year: int
     
     
+class ForecastTrendPoint(DefultBase):
+    date: Optional[datetime] = None
+    simulation_id: str
+    simulation_name: str
+    eaf: Optional[float] = None
+    efor: Optional[float] = None
+    sof: Optional[float] = None
+    edh: Optional[float] = None
+
+
 class SimulationQueryModel(CommonParams):
     status: Optional[str] = Field(None, max_length=20)
     

src/aeros_simulation/service.py

@@ -526,9 +526,7 @@ async def process_calc_results_streaming(
     
     # Parse nodeResultOuts array incrementally
     calc_results = ijson.items(response_stream, 'nodeResultOuts.item')
-    
-    raise Exception(calc_results)
-    
+
     async for result in calc_results:
         calc_obj = await create_calc_result_object(
             simulation_id, result, available_nodes, eq_update, db_session
@@ -843,10 +841,7 @@ async def save_simulation_result(
             status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e)
         )
 
-    # db_session.add_all(calc_objects)
-    # db_session.add_all(plot_objects)
-    
-    raise Exception(plot_result)
+    db_session.add_all(plot_objects)
 
     simulation = await get_simulation_by_id(
         db_session=db_session, simulation_id=simulation_id
@@ -1045,3 +1040,44 @@ async def update_simulation(*, db_session: DbSession, simulation_id: UUID, data:
     query = update(AerosSimulation).where(AerosSimulation.id == simulation_id).values(**data)
     await db_session.execute(query)
     await db_session.commit()
+
+
+async def get_forecast_trending(
+    *, db_session: DbSession, time_range: str, limit: int = 12
+) -> list:
+    """
+    Return EAF/EFOR/SOF/EDH for the last `limit` completed weekly or monthly
+    forecast simulations, oldest first (for chronological chart rendering).
+    """
+    name_prefix = f"Simulation_{time_range}_"
+    plant_node_name = "- TJB - Unit 3 -"
+
+    query = (
+        select(AerosSimulation, AerosSimulationCalcResult)
+        .join(
+            AerosSimulationCalcResult,
+            AerosSimulationCalcResult.aeros_simulation_id == AerosSimulation.id,
+        )
+        .join(AerosNode, AerosNode.id == AerosSimulationCalcResult.aeros_node_id)
+        .where(AerosSimulation.status == "completed")
+        .where(AerosSimulation.simulation_name.like(f"{name_prefix}%"))
+        .where(AerosNode.node_name == plant_node_name)
+        .order_by(AerosSimulation.completed_at.desc())
+        .limit(limit)
+    )
+
+    result = await db_session.execute(query)
+    rows = result.all()
+
+    return [
+        {
+            "date": sim.completed_at,
+            "simulation_id": str(sim.id),
+            "simulation_name": sim.simulation_name,
+            "eaf": calc.eaf,
+            "efor": calc.efor,
+            "sof": calc.sof,
+            "edh": calc.derating_hours,
+        }
+        for sim, calc in reversed(rows)  # oldest → newest for chart x-axis
+    ]