Merge pull request #236 from w7-mgfcode/fix/planner-model-exogenous-and-empty-dates

w7-mgfcode · web-flow · commit f09dec08bfde · 2026-05-19T14:18:30.000+02:00
fix(jobs,ui): reach model_exogenous + block empty assumption dates in the planner
diff --git a/app/features/jobs/schemas.py b/app/features/jobs/schemas.py
@@ -25,7 +25,7 @@ class JobCreate(BaseModel):
     **Job Types and Required Params**:
 
     - **train**: Train a forecasting model
-      - `model_type`: Required - 'naive', 'seasonal_naive', 'linear_regression', etc.
+      - `model_type`: Required - 'naive', 'seasonal_naive', 'moving_average', 'regression'.
       - `store_id`: Required - Store ID from /dimensions/stores
       - `product_id`: Required - Product ID from /dimensions/products
       - `start_date`: Required - Training data start (YYYY-MM-DD)
diff --git a/app/features/jobs/service.py b/app/features/jobs/service.py
@@ -426,6 +426,7 @@ async def _execute_train(
         from app.features.forecasting.schemas import (
             MovingAverageModelConfig,
             NaiveModelConfig,
+            RegressionModelConfig,
             SeasonalNaiveModelConfig,
         )
         from app.features.forecasting.service import ForecastingService
@@ -457,6 +458,12 @@ async def _execute_train(
         elif model_type == "moving_average":
             window_size = params.get("window_size", 7)
             config = MovingAverageModelConfig(window_size=window_size)
+        elif model_type == "regression":
+            config = RegressionModelConfig(
+                max_iter=params.get("max_iter", 200),
+                learning_rate=params.get("learning_rate", 0.05),
+                max_depth=params.get("max_depth", 6),
+            )
         else:
             msg = f"Unsupported model_type: {model_type}"
             raise ValueError(msg)
diff --git a/app/features/jobs/tests/test_service.py b/app/features/jobs/tests/test_service.py
@@ -8,6 +8,11 @@
 
 import math
 from datetime import date
+from typing import Any, cast
+from unittest.mock import AsyncMock, patch
+
+import pytest
+from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.features.backtesting.schemas import (
     BacktestResponse,
@@ -16,7 +21,9 @@
     SplitBoundary,
     SplitConfig,
 )
-from app.features.jobs.service import _finite, _shape_backtest_result
+from app.features.forecasting.schemas import RegressionModelConfig, TrainResponse
+from app.features.forecasting.service import ForecastingService
+from app.features.jobs.service import JobService, _finite, _shape_backtest_result
 
 
 def _fold(idx: int, mae: float, smape: float, wape: float, bias: float) -> FoldResult:
@@ -158,3 +165,59 @@ def test_finite_coerces_non_finite_values() -> None:
     assert _finite(math.nan) == 0.0
     assert _finite(math.inf) == 0.0
     assert _finite(-math.inf) == 0.0
+
+
+# =============================================================================
+# _execute_train regression-model support (#229)
+# =============================================================================
+
+
+def _fake_train_response(model_type: str) -> TrainResponse:
+    """Build a TrainResponse stub for mocking ForecastingService.train_model."""
+    return TrainResponse(
+        store_id=1,
+        product_id=1,
+        model_type=model_type,
+        model_path="/data/artifacts/model_abc123def456.joblib",
+        config_hash="cfg-hash",
+        n_observations=400,
+        train_start_date=date(2024, 1, 1),
+        train_end_date=date(2024, 12, 31),
+        duration_ms=12.0,
+    )
+
+
+_REGRESSION_PARAMS: dict[str, Any] = {
+    "model_type": "regression",
+    "store_id": 1,
+    "product_id": 1,
+    "start_date": "2024-01-01",
+    "end_date": "2024-12-31",
+}
+
+
+async def test_execute_train_builds_regression_config() -> None:
+    """A train job with model_type='regression' builds a RegressionModelConfig (#229)."""
+    fake = _fake_train_response("regression")
+    with patch.object(
+        ForecastingService, "train_model", new=AsyncMock(return_value=fake)
+    ) as mock_train:
+        result = await JobService()._execute_train(
+            db=cast(AsyncSession, AsyncMock()),
+            params=_REGRESSION_PARAMS,
+        )
+    assert mock_train.call_args is not None
+    config = mock_train.call_args.kwargs["config"]
+    assert isinstance(config, RegressionModelConfig)
+    assert result["model_type"] == "regression"
+    # run_id is parsed from the model_abc123def456.joblib artifact path.
+    assert result["run_id"] == "abc123def456"
+
+
+async def test_execute_train_rejects_unsupported_model_type() -> None:
+    """_execute_train still rejects a genuinely unsupported model_type (e.g. lightgbm)."""
+    with pytest.raises(ValueError, match="Unsupported model_type"):
+        await JobService()._execute_train(
+            db=cast(AsyncSession, AsyncMock()),
+            params={**_REGRESSION_PARAMS, "model_type": "lightgbm"},
+        )
diff --git a/frontend/src/lib/scenario-utils.test.ts b/frontend/src/lib/scenario-utils.test.ts
@@ -1,5 +1,6 @@
 import { describe, expect, it } from 'vitest'
 import {
+  assumptionDateErrors,
   buildMultiSeries,
   coverageLabel,
   coverageVariant,
@@ -143,3 +144,61 @@ describe('methodLabel', () => {
     expect(methodLabel('model_exogenous')).toBe('Model-driven')
   })
 })
+
+describe('assumptionDateErrors', () => {
+  const NONE = {
+    priceEnabled: false,
+    priceStart: '',
+    priceEnd: '',
+    promoEnabled: false,
+    promoStart: '',
+    promoEnd: '',
+  }
+
+  it('reports no errors when nothing is enabled', () => {
+    expect(assumptionDateErrors(NONE).hasErrors).toBe(false)
+  })
+
+  it('flags both price dates when price is enabled and blank', () => {
+    const e = assumptionDateErrors({ ...NONE, priceEnabled: true })
+    expect(e.priceStart).toBe(true)
+    expect(e.priceEnd).toBe(true)
+    expect(e.hasErrors).toBe(true)
+  })
+
+  it('clears price errors once both dates are filled', () => {
+    const e = assumptionDateErrors({
+      ...NONE,
+      priceEnabled: true,
+      priceStart: '2026-07-01',
+      priceEnd: '2026-07-14',
+    })
+    expect(e.hasErrors).toBe(false)
+  })
+
+  it('flags only the blank promotion date', () => {
+    const e = assumptionDateErrors({
+      ...NONE,
+      promoEnabled: true,
+      promoStart: '2026-07-01',
+      promoEnd: '',
+    })
+    expect(e.promoStart).toBe(false)
+    expect(e.promoEnd).toBe(true)
+    expect(e.hasErrors).toBe(true)
+  })
+
+  it('isolates errors per assumption (price ok, promo blank)', () => {
+    const e = assumptionDateErrors({
+      priceEnabled: true,
+      priceStart: '2026-07-01',
+      priceEnd: '2026-07-14',
+      promoEnabled: true,
+      promoStart: '',
+      promoEnd: '',
+    })
+    expect(e.priceStart).toBe(false)
+    expect(e.promoStart).toBe(true)
+    expect(e.hasErrors).toBe(true)
+  })
+})
diff --git a/frontend/src/lib/scenario-utils.ts b/frontend/src/lib/scenario-utils.ts
@@ -135,3 +135,41 @@ export function buildMultiSeries(comparison: MultiScenarioComparison): MultiSeri
 export function methodLabel(method: 'heuristic' | 'model_exogenous'): string {
   return method === 'model_exogenous' ? 'Model-driven' : 'Heuristic'
 }
+
+/** Form state for the date-bearing assumptions (price, promotion). */
+export interface AssumptionDateState {
+  priceEnabled: boolean
+  priceStart: string
+  priceEnd: string
+  promoEnabled: boolean
+  promoStart: string
+  promoEnd: string
+}
+
+/** Which enabled assumption date inputs are still blank. */
+export interface AssumptionDateErrors {
+  priceStart: boolean
+  priceEnd: boolean
+  promoStart: boolean
+  promoEnd: boolean
+  hasErrors: boolean
+}
+
+/**
+ * Flag every enabled Price/Promotion assumption whose From/To date is blank.
+ * The planner blocks Run/Save while `hasErrors` is true so the backend never
+ * receives an empty-string date (which fails Pydantic date validation → 422).
+ */
+export function assumptionDateErrors(state: AssumptionDateState): AssumptionDateErrors {
+  const priceStart = state.priceEnabled && !state.priceStart
+  const priceEnd = state.priceEnabled && !state.priceEnd
+  const promoStart = state.promoEnabled && !state.promoStart
+  const promoEnd = state.promoEnabled && !state.promoEnd
+  return {
+    priceStart,
+    priceEnd,
+    promoStart,
+    promoEnd,
+    hasErrors: priceStart || priceEnd || promoStart || promoEnd,
+  }
+}
diff --git a/frontend/src/pages/visualize/planner.tsx b/frontend/src/pages/visualize/planner.tsx
@@ -35,6 +35,7 @@ import {
 import { downloadCsv, toCsv } from '@/lib/csv-export'
 import { formatCurrency, formatNumber, getErrorMessage } from '@/lib/api'
 import {
+  assumptionDateErrors,
   buildMultiSeries,
   coverageLabel,
   coverageVariant,
@@ -73,8 +74,11 @@ export default function WhatIfPlannerPage() {
   const [selectedJobId, setSelectedJobId] = useState('')
   const [horizon, setHorizon] = useState(14)
   const { data: job } = useJob(selectedJobId, !!selectedJobId)
-  // A predict job's params.run_id is the baseline model artifact key.
-  const baselineRunId = typeof job?.params?.run_id === 'string' ? job.params.run_id : null
+  // A completed `train` job stores result.run_id — the model-artifact key
+  // POST /scenarios/simulate resolves. (This is NOT a registry run id.)
+  // A `regression` baseline routes the simulate call down the model_exogenous
+  // re-forecast branch; other model types fall back to the heuristic factor.
+  const baselineRunId = typeof job?.result?.run_id === 'string' ? job.result.run_id : null
 
   // -- Assumption form state ---------------------------------------------
   const [priceEnabled, setPriceEnabled] = useState(false)
@@ -97,6 +101,19 @@ export default function WhatIfPlannerPage() {
   const [lifecycleStage, setLifecycleStage] =
     useState<(typeof LIFECYCLE_STAGES)[number]>('maturity')
 
+  // -- Derived validation ------------------------------------------------
+  // Enabling Price/Promotion without filling both dates would submit empty
+  // strings — Pydantic date validation rejects those with an RFC 7807 422.
+  // Gate Run/Save on this so the form can never produce that request (#228).
+  const dateErrors = assumptionDateErrors({
+    priceEnabled,
+    priceStart,
+    priceEnd,
+    promoEnabled,
+    promoStart,
+    promoEnd,
+  })
+
   // -- Results / persistence state ---------------------------------------
   const [simulated, setSimulated] = useState<ScenarioComparison | null>(null)
   const [planName, setPlanName] = useState('')
@@ -152,7 +169,7 @@ export default function WhatIfPlannerPage() {
   }
 
   async function handleRun() {
-    if (!baselineRunId) return
+    if (!baselineRunId || dateErrors.hasErrors) return
     setRunError(null)
     setReloadId('')
     try {
@@ -169,7 +186,7 @@ export default function WhatIfPlannerPage() {
   }
 
   async function handleSave() {
-    if (!baselineRunId || !planName.trim()) return
+    if (!baselineRunId || !planName.trim() || dateErrors.hasErrors) return
     setRunError(null)
     try {
       await createScenario.mutateAsync({
@@ -245,12 +262,15 @@ export default function WhatIfPlannerPage() {
         <CardHeader>
           <CardTitle>1. Pick a baseline</CardTitle>
           <CardDescription>
-            Choose a completed prediction job — its model is the baseline this scenario adjusts.
+            Choose a completed training job — its model is the baseline this scenario
+            adjusts. A regression baseline is genuinely re-forecast through the model
+            (model-driven); naive, seasonal-naive and moving-average baselines use a
+            heuristic adjustment factor.
           </CardDescription>
         </CardHeader>
         <CardContent className="space-y-4">
           <JobPicker
-            jobType="predict"
+            jobType="train"
             selectedJobId={selectedJobId}
             onSelect={setSelectedJobId}
             autoSelectLatest
@@ -274,7 +294,7 @@ export default function WhatIfPlannerPage() {
           </div>
           {selectedJobId && !baselineRunId && (
             <p className="text-sm text-muted-foreground">
-              The selected job has no model artifact — pick a completed predict job.
+              The selected job has no model artifact — pick a completed train job.
             </p>
           )}
         </CardContent>
@@ -317,6 +337,9 @@ export default function WhatIfPlannerPage() {
                     value={priceStart}
                     onChange={(event) => setPriceStart(event.target.value)}
                   />
+                  {dateErrors.priceStart && (
+                    <p className="text-xs text-destructive">Required</p>
+                  )}
                 </div>
                 <div className="space-y-1">
                   <span className="text-xs text-muted-foreground">To</span>
@@ -326,6 +349,9 @@ export default function WhatIfPlannerPage() {
                     value={priceEnd}
                     onChange={(event) => setPriceEnd(event.target.value)}
                   />
+                  {dateErrors.priceEnd && (
+                    <p className="text-xs text-destructive">Required</p>
+                  )}
                 </div>
               </div>
             )}
@@ -368,6 +394,9 @@ export default function WhatIfPlannerPage() {
                     value={promoStart}
                     onChange={(event) => setPromoStart(event.target.value)}
                   />
+                  {dateErrors.promoStart && (
+                    <p className="text-xs text-destructive">Required</p>
+                  )}
                 </div>
                 <div className="space-y-1">
                   <span className="text-xs text-muted-foreground">To</span>
@@ -377,6 +406,9 @@ export default function WhatIfPlannerPage() {
                     value={promoEnd}
                     onChange={(event) => setPromoEnd(event.target.value)}
                   />
+                  {dateErrors.promoEnd && (
+                    <p className="text-xs text-destructive">Required</p>
+                  )}
                 </div>
               </div>
             )}
@@ -462,7 +494,10 @@ export default function WhatIfPlannerPage() {
           </div>
 
           <div className="flex flex-wrap items-center gap-3 border-t pt-4">
-            <Button onClick={handleRun} disabled={!baselineRunId || simulate.isPending}>
+            <Button
+              onClick={handleRun}
+              disabled={!baselineRunId || simulate.isPending || dateErrors.hasErrors}
+            >
               {simulate.isPending ? (
                 <Loader2 className="mr-2 h-4 w-4 animate-spin" />
               ) : (
@@ -593,7 +628,12 @@ export default function WhatIfPlannerPage() {
                 </div>
                 <Button
                   onClick={handleSave}
-                  disabled={!baselineRunId || !planName.trim() || createScenario.isPending}
+                  disabled={
+                    !baselineRunId ||
+                    !planName.trim() ||
+                    createScenario.isPending ||
+                    dateErrors.hasErrors
+                  }
                 >
                   {createScenario.isPending ? (
                     <Loader2 className="mr-2 h-4 w-4 animate-spin" />
