fix(simple_metrics): skip invalid interval_minutes and restart a malformed healthy_streak (SIENTIAPDE-2191)

- interval_minutes is untyped Mongo config: a string or null now warns and
  skips the adaptive state instead of failing every run (TypeError).
- A hand-edited healthy_streak (null, text, inf) restarts the count and keeps
  escalated, instead of raising on every run.
- README: step 4 runs on every schedule, so a MongoDB failure fails the run.

README.md

@@ -489,7 +489,7 @@ The **SimpleMetrics** workflow calculates regression metrics (RMSE, MSE, MAE, R
 1. **Data Loading**: Loads prediction vs target data via a JOIN query
 2. **Metrics Calculation**: Calculates configured regression metrics; alerts on `simple_metrics_thresholds` breaches (one alert per model, the message names the window) unless the window has fewer rows than `simple_metrics_min_samples`
 3. **Data Export**: Exports metrics to PostgreSQL
-4. **Adaptive State**: when the schedule's `pipelines` doc has `frequency_alert`, escalates `adaptive_state` on a breach and recovers after the window is renewed without one (`min(12, ceil(interval_minutes / frequency_alert))` runs, at least 1; empty, under-sampled or threshold-less windows count as healthy). The orchestrator runs the schedule at `frequency_alert` while escalated
+4. **Adaptive State**: when the schedule's `pipelines` doc has `frequency_alert`, escalates `adaptive_state` on a breach and recovers after the window is renewed without one (`min(12, ceil(interval_minutes / frequency_alert))` runs, at least 1; empty, under-sampled or threshold-less windows count as healthy). The orchestrator runs the schedule at `frequency_alert` while escalated. Runs on every schedule (it reads the `pipelines` doc to check for `frequency_alert`), so a MongoDB failure here fails the run; the metrics are already exported by then
 
 #### Architecture Diagram
 ```mermaid

laborious/activities/model_metrics.py

@@ -85,7 +85,10 @@ def next_adaptive_state(state: dict[str, Any], breached: bool, runs: int) -> dic
         return {'escalated': True, 'healthy_streak': 0}
     if not state.get('escalated'):
         return {'escalated': False, 'healthy_streak': 0}
-    streak = int(state.get('healthy_streak', 0)) + 1
+    try:
+        streak = int(state.get('healthy_streak', 0)) + 1
+    except (TypeError, ValueError, OverflowError):
+        streak = 1  # hand-edited streak (null, text, inf): restart the count, stay escalated
     if streak >= runs:
         return {'escalated': False, 'healthy_streak': 0}
     return {'escalated': True, 'healthy_streak': streak}

laborious/activities/mongo.py

@@ -192,11 +192,14 @@ class MongoActivities(SientiaMonitoring):
 
         try:
             runs = recovery_runs(input_data['interval_minutes'], str(frequency_alert))
-        except ValueError:
-            # Config error, not a failure: the orchestrator ignores this value too (keeps
-            # `frequency`) and already sends SIMPLE_METRICS_FREQUENCY_ALERT_BELOW_FLOOR for it.
+        except (TypeError, ValueError):
+            # Config error, not a failure: the orchestrator ignores an invalid `frequency_alert`
+            # too (keeps `frequency`) and already sends SIMPLE_METRICS_FREQUENCY_ALERT_BELOW_FLOOR
+            # for it. `interval_minutes` is untyped Mongo config as well (e.g. "60" or null).
             self.warning(
-                f'Invalid frequency_alert={frequency_alert!r}: adaptive state skipped', metadata
+                f'Invalid frequency_alert={frequency_alert!r} or '
+                f'interval_minutes={input_data["interval_minutes"]!r}: adaptive state skipped',
+                metadata,
             )
             return None
 

tests/laborious/activities/test_model_metrics.py

@@ -1267,6 +1267,9 @@ def _state(escalated: bool, streak: int) -> dict:
         (_state(True, 2), False, 3, _state(False, 0)),  # N-th healthy run recovers
         (_state(True, 2), True, 3, _state(True, 0)),  # breach resets the streak
         (_state(True, 0), False, 1, _state(False, 0)),  # N=1 recovers on first healthy run
+        (_state(True, None), False, 3, _state(True, 1)),  # hand-edited streak restarts
+        (_state(True, 'x'), False, 3, _state(True, 1)),
+        (_state(True, float('inf')), False, 3, _state(True, 1)),
     ],
 )
 def test_next_adaptive_state(state, breached, runs, expected):

tests/laborious/activities/test_mongo.py

@@ -322,6 +322,22 @@ def test_adaptive_state_invalid_frequency_alert_is_skipped(
     mongo_activities.warning.assert_called_once()
 
 
+@mark.parametrize('interval_minutes', ['60', None])
+def test_adaptive_state_invalid_interval_minutes_is_skipped(
+    mongo_activities, mongo, interval_minutes
+):
+    # Untyped Mongo config: "60" * 60 is a string, None * 60 a TypeError.
+    mongo.find_one.return_value = _pipeline(frequency_alert='5m')
+
+    result = mongo_activities.update_simple_metrics_adaptive_state(
+        {**_BREACH_INPUT, 'interval_minutes': interval_minutes}
+    )
+
+    assert result is None
+    mongo.update_one.assert_not_called()
+    mongo_activities.warning.assert_called_once()
+
+
 @mark.parametrize('adaptive_state', ['garbage', ['escalated']])
 def test_adaptive_state_malformed_state_is_not_escalated(mongo_activities, mongo, adaptive_state):
     mongo.find_one.return_value = _pipeline(frequency_alert='5m', adaptive_state=adaptive_state)