Remove SEBA from everest

src/ert/run_models/everest_run_model.py

@@ -21,7 +21,6 @@
 from ropt.evaluator import EvaluatorContext, EvaluatorResult
 from ropt.plan import BasicOptimizer
 from ropt.plan import Event as OptimizerEvent
-from seba_sqlite import SqliteStorage
 from typing_extensions import TypedDict
 
 from _ert.events import EESnapshot, EESnapshotUpdate, Event
@@ -185,23 +184,11 @@ def run_experiment(
             / "OPT_DEFAULT.out",
         )
 
-        # The SqliteStorage object is used to store optimization results from
-        # Seba in an sqlite database. It reacts directly to events emitted by
-        # Seba and is not called by Everest directly. The stored results are
-        # accessed by Everest via separate SebaSnapshot objects.
-        # This mechanism is outdated and not supported by the ropt package. It
-        # is retained for now via the seba_sqlite package.
-        seba_storage = SqliteStorage(  # type: ignore
-            optimizer, self._everest_config.optimization_output_dir
-        )
-
         # Run the optimization:
         optimizer_exit_code = optimizer.run().exit_code
 
         # Extract the best result from the storage.
-        self._result = OptimalResult.from_seba_optimal_result(
-            seba_storage.get_optimal_result()  # type: ignore
-        )
+        self._result = self.ever_storage.get_optimal_result()
 
         if self._exit_code is None:
             match optimizer_exit_code:

src/everest/everest_storage.py

@@ -18,7 +18,6 @@
 from ropt.enums import EventType
 from ropt.plan import BasicOptimizer, Event
 from ropt.results import FunctionResults, GradientResults, convert_to_maximize
-from seba_sqlite import sqlite_storage
 
 logger = logging.getLogger(__name__)
 
@@ -32,17 +31,6 @@ class OptimalResult:
     controls: list[Any]
     total_objective: float
 
-    @staticmethod
-    def from_seba_optimal_result(
-        o: sqlite_storage.OptimalResult | None = None,
-    ) -> OptimalResult | None:
-        if o is None:
-            return None
-
-        return OptimalResult(
-            batch=o.batch + 1, controls=o.controls, total_objective=o.total_objective
-        )
-
 
 def try_read_df(path: Path) -> polars.DataFrame | None:
     return polars.read_parquet(path) if path.exists() else None