Merge pull request #615 from moririn2528/settting-api

add preference feedback component api

docs/api.rst

@@ -44,6 +44,7 @@ Preferential Optimization
    optuna_dashboard.preferential.create_study
    optuna_dashboard.preferential.load_study
    optuna_dashboard.preferential.PreferentialStudy
+   optuna_dashboard.register_preference_feedback_component
 
 Streamlit
 -----------------

optuna_dashboard/__init__.py

@@ -14,6 +14,7 @@ from ._form_widget import TextInputWidget  # noqa
 from ._named_objectives import set_objective_names  # noqa
 from ._note import get_note  # noqa
 from ._note import save_note  # noqa
+from ._preference_setting import register_preference_feedback_component  # noqa
 
 
 __version__ = "0.13.0b1"

optuna_dashboard/_app.py

@@ -28,6 +28,7 @@ from ._cached_extra_study_property import get_cached_extra_study_property
 from ._custom_plot_data import get_plotly_graph_objects
 from ._importance import get_param_importance_from_trials_cache
 from ._pareto_front import get_pareto_front_trials
+from ._preference_setting import _register_preference_feedback_component
 from ._preferential_history import NewHistory
 from ._preferential_history import PreferenceHistoryNotFound
 from ._preferential_history import remove_history
@@ -315,6 +316,28 @@ def create_app(
         response.status = 204
         return {}
 
+    @app.put("/api/studies/<study_id:int>/preference_feedback_component_type")
+    @json_api_view
+    def put_preference_feedback_component_type(study_id: int) -> dict[str, Any]:
+        try:
+            component_type = request.json.get("type", "")
+            artifact_key = request.json.get("artifact_key", None)
+        except ValueError:
+            response.status = 400
+            return {"reason": "invalid request."}
+        if component_type not in ["note", "artifact"]:
+            response.status = 400
+            return {"reason": "component_type must be either 'Note' or 'Artifact'."}
+
+        _register_preference_feedback_component(
+            study_id=study_id,
+            storage=storage,
+            component_type=component_type,
+            artifact_key=artifact_key,
+        )
+        response.status = 204
+        return {}
+
     @app.delete("/api/studies/<study_id:int>/preference/<history_id>")
     @json_api_view
     def remove_preference(study_id: int, history_id: str) -> dict[str, Any]:

optuna_dashboard/_preference_setting.py

@@ -0,0 +1,67 @@
+from __future__ import annotations
+
+from typing import Any
+from typing import TYPE_CHECKING
+
+from optuna.storages import BaseStorage
+
+from .preferential._study import PreferentialStudy
+
+
+if TYPE_CHECKING:
+    from typing import Literal
+
+    OUTPUT_COMPONENT_TYPE = Literal["note", "artifact"]
+
+_SYSTEM_ATTR_FEEDBACK_COMPONENT = "preference:component"
+
+
+def _register_preference_feedback_component(
+    study_id: int,
+    storage: BaseStorage,
+    component_type: OUTPUT_COMPONENT_TYPE,
+    artifact_key: str | None = None,
+) -> None:
+    value: dict[str, Any] = {"type": component_type}
+    if artifact_key is not None:
+        value["artifact_key"] = artifact_key
+    storage.set_study_system_attr(
+        study_id=study_id,
+        key=_SYSTEM_ATTR_FEEDBACK_COMPONENT,
+        value=value,
+    )
+
+
+def register_preference_feedback_component(
+    study: PreferentialStudy,
+    component_type: OUTPUT_COMPONENT_TYPE,
+    artifact_key: str | None = None,
+) -> None:
+    """Register a preference feedback component to the study.
+
+    With this feature, you can change the component, displayed on the
+    human feedback pages. By default, the Markdown note (``component_type="note"``)
+    is displayed.  If you specify ``component_type="artifact"``, the viewer for the
+    specified artifact file will be displayed.
+    Args:
+        study:
+            The study to register the preference feedback component.
+        component_type:
+            The component type, displayed on the human feedback pages
+            (default: ``"note"``).
+        user_attr_artifact_key:
+            This option is required when the ``component_type`` is ``"artifact"``.
+            The user attribute, which is specified this field, must contain the
+            ``artifact``id you want to display on the human feedback page.
+    """
+    if component_type == "artifact":
+        assert (
+            artifact_key is not None
+        ), "artifact_key must be specified when component_type is Artifact"
+
+    _register_preference_feedback_component(
+        study_id=study._study._study_id,
+        storage=study._study._storage,
+        component_type=component_type,
+        artifact_key=artifact_key,
+    )

optuna_dashboard/_serializer.py

@@ -15,6 +15,7 @@ from optuna.trial import FrozenTrial
 from . import _note as note
 from ._form_widget import get_form_widgets_json
 from ._named_objectives import get_objective_names
+from ._preference_setting import _SYSTEM_ATTR_FEEDBACK_COMPONENT
 from ._preferential_history import _SYSTEM_ATTR_PREFIX_HISTORY
 from .artifact._backend import list_trial_artifacts
 from .preferential._study import _SYSTEM_ATTR_PREFERENTIAL_STUDY
@@ -165,6 +166,9 @@ def serialize_study_detail(
     if form_widgets:
         serialized["form_widgets"] = form_widgets
     if serialized["is_preferential"]:
+        serialized["feedback_component_type"] = system_attrs.get(
+            _SYSTEM_ATTR_FEEDBACK_COMPONENT, {}
+        )
         serialized["preference_history"] = serialize_preference_history(system_attrs)
         serialized["preferences"] = get_preferences(system_attrs)
         serialized["skipped_trials"] = skipped_trials

python_tests/test_api.py

@@ -8,6 +8,7 @@ from optuna import get_all_study_summaries
 from optuna.study import StudyDirection
 from optuna_dashboard._app import create_app
 from optuna_dashboard._app import create_new_study
+from optuna_dashboard._preference_setting import register_preference_feedback_component
 from optuna_dashboard._preferential_history import NewHistory
 from optuna_dashboard._preferential_history import remove_history
 from optuna_dashboard._preferential_history import report_history
@@ -183,6 +184,36 @@ class APITestCase(TestCase):
         )
         self.assertEqual(status, 400)
 
+    def test_change_component(self) -> None:
+        storage = optuna.storages.InMemoryStorage()
+        study = create_study(storage=storage, n_generate=3)
+        register_preference_feedback_component(study, "note")
+        for _ in range(3):
+            study.ask()
+
+        app = create_app(storage)
+        study_id = study._study._study_id
+        status, _, _ = send_request(
+            app,
+            f"/api/studies/{study_id}/preference_feedback_component_type",
+            "PUT",
+            body=json.dumps({"type": "artifact", "artifact_key": "image"}),
+            content_type="application/json",
+        )
+        self.assertEqual(status, 204)
+
+        status, _, body = send_request(
+            app,
+            f"/api/studies/{study_id}",
+            "GET",
+            content_type="application/json",
+        )
+        self.assertEqual(status, 200)
+
+        study_detail = json.loads(body)
+        assert study_detail["feedback_component_type"]["type"] == "artifact"
+        assert study_detail["feedback_component_type"]["artifact_key"] == "image"
+
     def test_skip_trial(self) -> None:
         storage = optuna.storages.InMemoryStorage()
         study = create_study(n_generate=4, storage=storage)

python_tests/test_preference_setting.py

@@ -0,0 +1,20 @@
+from __future__ import annotations
+
+from unittest import TestCase
+
+import optuna
+from optuna_dashboard._preference_setting import _SYSTEM_ATTR_FEEDBACK_COMPONENT
+from optuna_dashboard._preference_setting import register_preference_feedback_component
+from optuna_dashboard.preferential._study import PreferentialStudy
+
+
+class FeedbackSettingTestCase(TestCase):
+    def test_widget_to_dict_from_dict(self) -> None:
+        study = PreferentialStudy(optuna.create_study())
+        register_preference_feedback_component(study, "artifact", "image_key")
+        system_attrs = study._study.system_attrs
+        feedback_type = system_attrs.get(_SYSTEM_ATTR_FEEDBACK_COMPONENT, {})
+        assert "type" in feedback_type
+        assert feedback_type["type"] == "artifact"
+        assert "artifact_key" in feedback_type
+        assert feedback_type["artifact_key"] == "image_key"