diff --git a/docs/api.rst b/docs/api.rst
index 18f8bc72..e26dcfd6 100644
--- a/docs/api.rst
+++ b/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.preferential.samplers.gp.PreferentialGPSampler
    optuna_dashboard.register_preference_feedback_component
 
 Streamlit
diff --git a/optuna_dashboard/preferential/samplers/gp.py b/optuna_dashboard/preferential/samplers/gp.py
index 2e782b68..beb5b7c2 100644
--- a/optuna_dashboard/preferential/samplers/gp.py
+++ b/optuna_dashboard/preferential/samplers/gp.py
@@ -284,6 +284,26 @@ class _PreferentialGP:
 
 
 class PreferentialGPSampler(optuna.samplers.BaseSampler):
+    """Sampler for preferential optimization using Gaussian process.
+
+    The sampling algorithm is based on `Takeno et al., 2023 <https://arxiv.org/abs/2302.01513>`_.
+    This sampler uses BoTorch to optimize acquisition function.
+
+    Args:
+        kernel:
+            Kernel that computes the covariance on the Gaussian process. Defaults to
+            Matern 3/2 Kernel + ARD.
+        noise_prior:
+            Prior of the observation noise. Defaults to gamma prior.
+        independent_sampler:
+            A :class:`~optuna.samplers.BaseSampler` instance that is used for independent
+            sampling. The parameters not contained in the relative search space are sampled
+            by this sampler. If :obj:`None` is specified,
+            :class:`~optuna.samplers.RandomSampler` is used as the default.
+        seed:
+            Seed for random number generator.
+    """
+
     def __init__(
         self,
         *,
diff --git a/pyproject.toml b/pyproject.toml
index 4eff6f1f..9d8500dc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,6 +36,7 @@ dynamic = ["version"]
 [project.optional-dependencies]
 docs = [
     "boto3",
+    "botorch",
     "streamlit",
     "sphinx",
     "sphinx_rtd_theme",