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TileDB-Inc · Aug 28, 2024 · 6bf16cb · 6bf16cb
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diff --git a/docs/documentation/reference/flat_index.html b/docs/documentation/reference/flat_index.html
@@ -359,16 +359,16 @@ <h2 class="anchored" data-anchor-id="functions">Functions</h2>
 </table>
 <section id="tiledb.vector_search.flat_index.create" class="level3">
 <h3 class="anchored" data-anchor-id="tiledb.vector_search.flat_index.create">create</h3>
-<p><code>vector_search.flat_index.create(uri, dimensions, vector_type, group_exists=False, config=None, storage_version=STORAGE_VERSION, distance_metric=vspy.DistanceMetric.L2, **kwargs)</code></p>
+<p><code>vector_search.flat_index.create(uri, dimensions, vector_type, group_exists=False, config=None, storage_version=STORAGE_VERSION, distance_metric=vspy.DistanceMetric.SUM_OF_SQUARES, **kwargs)</code></p>
 <p>Creates an empty FlatIndex.</p>
 <section id="parameters-2" class="level4">
 <h4 class="anchored" data-anchor-id="parameters-2">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
 <col style="width: 9%">
-<col style="width: 16%">
-<col style="width: 60%">
-<col style="width: 13%">
+<col style="width: 15%">
+<col style="width: 57%">
+<col style="width: 18%">
 </colgroup>
 <thead>
 <tr class="header">
@@ -419,7 +419,7 @@ <h4 class="anchored" data-anchor-id="parameters-2">Parameters</h4>
 <td><code>distance_metric</code></td>
 <td>vspy.DistanceMetric</td>
 <td>Distance metric to use for the index. If not provided, use L2 distance.</td>
-<td><code>vspy.DistanceMetric.L2</code></td>
+<td><code>vspy.DistanceMetric.SUM_OF_SQUARES</code></td>
 </tr>
 </tbody>
 </table>

diff --git a/docs/documentation/reference/ingestion.html b/docs/documentation/reference/ingestion.html
@@ -229,16 +229,16 @@ <h2 class="anchored" data-anchor-id="functions">Functions</h2>
 </table>
 <section id="tiledb.vector_search.ingestion.ingest" class="level3">
 <h3 class="anchored" data-anchor-id="tiledb.vector_search.ingestion.ingest">ingest</h3>
-<p><code>vector_search.ingestion.ingest(index_type, index_uri, *, input_vectors=None, source_uri=None, source_type=None, external_ids=None, external_ids_uri='', external_ids_type=None, updates_uri=None, index_timestamp=None, config=None, namespace=None, size=-1, partitions=-1, num_subspaces=-1, l_build=-1, r_max_degree=-1, training_sampling_policy=TrainingSamplingPolicy.FIRST_N, copy_centroids_uri=None, training_sample_size=-1, training_input_vectors=None, training_source_uri=None, training_source_type=None, workers=-1, input_vectors_per_work_item=-1, max_tasks_per_stage=-1, input_vectors_per_work_item_during_sampling=-1, max_sampling_tasks=-1, storage_version=STORAGE_VERSION, verbose=False, trace_id=None, use_sklearn=True, mode=Mode.LOCAL, acn=None, ingest_resources=None, consolidate_partition_resources=None, copy_centroids_resources=None, random_sample_resources=None, kmeans_resources=None, compute_new_centroids_resources=None, assign_points_and_partial_new_centroids_resources=None, write_centroids_resources=None, partial_index_resources=None, distance_metric=vspy.DistanceMetric.L2, normalized=False, **kwargs)</code></p>
+<p><code>vector_search.ingestion.ingest(index_type, index_uri, *, input_vectors=None, source_uri=None, source_type=None, external_ids=None, external_ids_uri='', external_ids_type=None, updates_uri=None, index_timestamp=None, config=None, namespace=None, size=-1, partitions=-1, num_subspaces=-1, l_build=-1, r_max_degree=-1, training_sampling_policy=TrainingSamplingPolicy.FIRST_N, copy_centroids_uri=None, training_sample_size=-1, training_input_vectors=None, training_source_uri=None, training_source_type=None, workers=-1, input_vectors_per_work_item=-1, max_tasks_per_stage=-1, input_vectors_per_work_item_during_sampling=-1, max_sampling_tasks=-1, storage_version=STORAGE_VERSION, verbose=False, trace_id=None, use_sklearn=True, mode=Mode.LOCAL, acn=None, ingest_resources=None, consolidate_partition_resources=None, copy_centroids_resources=None, random_sample_resources=None, kmeans_resources=None, compute_new_centroids_resources=None, assign_points_and_partial_new_centroids_resources=None, write_centroids_resources=None, partial_index_resources=None, distance_metric=vspy.DistanceMetric.SUM_OF_SQUARES, normalized=False, **kwargs)</code></p>
 <p>Ingest vectors into TileDB.</p>
 <section id="parameters" class="level4">
 <h4 class="anchored" data-anchor-id="parameters">Parameters</h4>
 <table class="caption-top table">
 <colgroup>
-<col style="width: 10%">
+<col style="width: 9%">
 <col style="width: 6%">
-<col style="width: 78%">
-<col style="width: 4%">
+<col style="width: 76%">
+<col style="width: 7%">
 </colgroup>
 <thead>
 <tr class="header">
@@ -504,8 +504,8 @@ <h4 class="anchored" data-anchor-id="parameters">Parameters</h4>
 <tr class="odd">
 <td><code>distance_metric</code></td>
 <td>vspy.DistanceMetric</td>
-<td>Distance metric to use for the index, defaults to ‘vspy.DistanceMetric.L2’. Options are ‘vspy.DistanceMetric.L2’, ‘vspy.DistanceMetric.INNER_PRODUCT’, ‘vspy.DistanceMetric.COSINE’.</td>
-<td><code>vspy.DistanceMetric.L2</code></td>
+<td>Distance metric to use for the index, defaults to ‘vspy.DistanceMetric.SUM_OF_SQUARES’. Options are ‘vspy.DistanceMetric.SUM_OF_SQUARES’, ‘vspy.DistanceMetric.INNER_PRODUCT’, ‘vspy.DistanceMetric.COSINE’, ‘vspy.DistanceMetric.L2’.</td>
+<td><code>vspy.DistanceMetric.SUM_OF_SQUARES</code></td>
 </tr>
 </tbody>
 </table>

diff --git a/docs/documentation/reference/ivf_flat_index.html b/docs/documentation/reference/ivf_flat_index.html
@@ -425,7 +425,7 @@ <h2 class="anchored" data-anchor-id="functions">Functions</h2>
 </table>
 <section id="tiledb.vector_search.ivf_flat_index.create" class="level3">
 <h3 class="anchored" data-anchor-id="tiledb.vector_search.ivf_flat_index.create">create</h3>
-<p><code>vector_search.ivf_flat_index.create(uri, dimensions, vector_type, group_exists=False, config=None, storage_version=STORAGE_VERSION, distance_metric=vspy.DistanceMetric.L2, **kwargs)</code></p>
+<p><code>vector_search.ivf_flat_index.create(uri, dimensions, vector_type, group_exists=False, config=None, storage_version=STORAGE_VERSION, distance_metric=vspy.DistanceMetric.SUM_OF_SQUARES, **kwargs)</code></p>
 <p>Creates an empty IVFFlatIndex.</p>
 <section id="parameters-2" class="level4">
 <h4 class="anchored" data-anchor-id="parameters-2">Parameters</h4>

diff --git a/docs/documentation/reference/vamana_index.html b/docs/documentation/reference/vamana_index.html
@@ -358,7 +358,7 @@ <h2 class="anchored" data-anchor-id="functions">Functions</h2>
 </table>
 <section id="tiledb.vector_search.vamana_index.create" class="level3">
 <h3 class="anchored" data-anchor-id="tiledb.vector_search.vamana_index.create">create</h3>
-<p><code>vector_search.vamana_index.create(uri, dimensions, vector_type, l_build=L_BUILD_DEFAULT, r_max_degree=R_MAX_DEGREE_DEFAULT, config=None, storage_version=STORAGE_VERSION, distance_metric=vspy.DistanceMetric.L2, **kwargs)</code></p>
+<p><code>vector_search.vamana_index.create(uri, dimensions, vector_type, l_build=L_BUILD_DEFAULT, r_max_degree=R_MAX_DEGREE_DEFAULT, config=None, storage_version=STORAGE_VERSION, distance_metric=vspy.DistanceMetric.SUM_OF_SQUARES, **kwargs)</code></p>
 <p>Creates an empty VamanaIndex.</p>
 <section id="parameters-2" class="level4">
 <h4 class="anchored" data-anchor-id="parameters-2">Parameters</h4>