scikit-learn
diff --git a/‎doc/modules/array_api.rst
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diff --git a/‎doc/whats_new/v1.6.rst
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diff --git a/‎sklearn/metrics/pairwise.py
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diff --git a/‎sklearn/metrics/tests/test_common.py
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diff --git a/‎sklearn/utils/_array_api.py
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@@ -123,6 +123,7 @@ Metrics
 - :func:`sklearn.metrics.pairwise.additive_chi2_kernel`
 - :func:`sklearn.metrics.pairwise.chi2_kernel`
 - :func:`sklearn.metrics.pairwise.cosine_similarity`
+- :func:`sklearn.metrics.pairwise.cosine_distances`
 - :func:`sklearn.metrics.pairwise.euclidean_distances` (see :ref:`device_support_for_float64`)
 - :func:`sklearn.metrics.pairwise.paired_cosine_distances`
 - :func:`sklearn.metrics.pairwise.rbf_kernel` (see :ref:`device_support_for_float64`)
 
@@ -43,6 +43,7 @@ See :ref:`array_api` for more details.
 - :func:`sklearn.metrics.pairwise.additive_chi2_kernel` :pr:`29144` by :user:`Yaroslav Korobko <Tialo>`;
 - :func:`sklearn.metrics.pairwise.chi2_kernel` :pr:`29267` by :user:`Yaroslav Korobko <Tialo>`;
 - :func:`sklearn.metrics.pairwise.cosine_similarity` :pr:`29014` by :user:`Edoardo Abati <EdAbati>`;
+- :func:`sklearn.metrics.pairwise.cosine_distances` :pr:`29265` by :user:`Emily Chen <EmilyXinyi>`;
 - :func:`sklearn.metrics.pairwise.euclidean_distances` :pr:`29433` by :user:`Omar Salman <OmarManzoor>`;
 - :func:`sklearn.metrics.pairwise.paired_cosine_distances` :pr:`29112` by :user:`Edoardo Abati <EdAbati>`;
 - :func:`sklearn.metrics.pairwise.rbf_kernel` :pr:`29433` by :user:`Omar Salman <OmarManzoor>`.
 
@@ -22,6 +22,7 @@
     gen_even_slices,
 )
 from ..utils._array_api import (
+    _clip,
     _fill_or_add_to_diagonal,
     _find_matching_floating_dtype,
     _is_numpy_namespace,
@@ -1139,15 +1140,17 @@ def cosine_distances(X, Y=None):
     array([[1.     , 1.     ],
            [0.42..., 0.18...]])
     """
+    xp, _ = get_namespace(X, Y)
+
     # 1.0 - cosine_similarity(X, Y) without copy
     S = cosine_similarity(X, Y)
     S *= -1
     S += 1
-    np.clip(S, 0, 2, out=S)
+    S = _clip(S, 0, 2, xp)
     if X is Y or Y is None:
         # Ensure that distances between vectors and themselves are set to 0.0.
         # This may not be the case due to floating point rounding errors.
-        np.fill_diagonal(S, 0.0)
+        _fill_or_add_to_diagonal(S, 0.0, xp, add_value=False)
     return S
 
 
 
@@ -54,6 +54,7 @@
 from sklearn.metrics.pairwise import (
     additive_chi2_kernel,
     chi2_kernel,
+    cosine_distances,
     cosine_similarity,
     euclidean_distances,
     paired_cosine_distances,
@@ -2016,6 +2017,7 @@ def check_array_api_metric_pairwise(metric, array_namespace, device, dtype_name)
     mean_gamma_deviance: [check_array_api_regression_metric],
     max_error: [check_array_api_regression_metric],
     chi2_kernel: [check_array_api_metric_pairwise],
+    cosine_distances: [check_array_api_metric_pairwise],
     euclidean_distances: [check_array_api_metric_pairwise],
     rbf_kernel: [check_array_api_metric_pairwise],
 }
 
@@ -791,6 +791,19 @@ def _nanmax(X, axis=None, xp=None):
         return X
 
 
+def _clip(S, min_val, max_val, xp):
+    # TODO: remove this method and change all usage once we move to array api 2023.12
+    # https://data-apis.org/array-api/2023.12/API_specification/generated/array_api.clip.html#clip
+    if _is_numpy_namespace(xp):
+        return numpy.clip(S, min_val, max_val)
+    else:
+        min_arr = xp.asarray(min_val, dtype=S.dtype)
+        max_arr = xp.asarray(max_val, dtype=S.dtype)
+        S = xp.where(S < min_arr, min_arr, S)
+        S = xp.where(S > max_arr, max_arr, S)
+        return S
+
+
 def _asarray_with_order(
     array, dtype=None, order=None, copy=None, *, xp=None, device=None
 ):