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PHPLIB-1789: Add autoEmbed type in VectorSearchIndexShape #1926

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Merged
GromNaN merged 1 commit into from
Jun 16, 2026
Merged

PHPLIB-1789: Add autoEmbed type in VectorSearchIndexShape #1926

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1 change: 1 addition & 0 deletions src/Collection.php
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Original file line number Diff line number Diff line change
Expand Up @@ -109,6 +109,7 @@
* @psalm-type VectorSearchIndexShape = array{
* fields: list<
* array{type: 'vector', path: string, numDimensions: int, similarity: 'euclidean'|'cosine'|'dotProduct', quantization?: 'none'|'scalar'|'binary', indexingMethod?: 'flat'|'hnsw', hnswOptions?: array{maxEdges?: int, numEdgeCandidates?: int}} |
* array{type: 'autoEmbed', modality: 'text', path: string, model: string, numDimensions?: int, quantization?: 'float'|'scalar'|'binary'|'binaryNoRescore', similarity?: 'euclidean'|'cosine'|'dotProduct', indexingMethod?: 'flat'|'hnsw', hnswOptions?: array{maxEdges?: int, numEdgeCandidates?: int}} |

@paulinevos paulinevos Jun 16, 2026

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Can we multiline these types of shapes with a lot of different fields? Would make it easier to read the diff

@GromNaN GromNaN Jun 16, 2026

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I have mixed feelings about it, because it also makes the docblock very, very long.

@paulinevos paulinevos Jun 18, 2026

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True, but now it's also long, but horizontally, and hard to read 😅 But I see what you mean. It's not aesthetically pleasing but will make it easier to see what's changed.

* array{type: 'filter', path: string}
* >,
* storedSource?: bool|array{include: list<string>}|array{exclude: list<string>},
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44 changes: 44 additions & 0 deletions tests/Type/SearchIndexShapes.php
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Expand Up @@ -226,4 +226,48 @@ public function vectorSearchIndexWithFlatIndexingMethod(Collection $collection):
['name' => 'my_flat_index', 'type' => 'vectorSearch'],
);
}

/** @see https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-type/ */
public function autoEmbedVectorSearchIndex(Collection $collection): void
{
$collection->createSearchIndex(
[
'fields' => [
[
'type' => 'autoEmbed',
'modality' => 'text',
'path' => 'description',
'model' => 'voyage-4',
],
],
],
['name' => 'my_auto_embed_index', 'type' => 'vectorSearch'],
);
}

/** @see https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-type/ */
public function autoEmbedVectorSearchIndexWithOptions(Collection $collection): void
{
$collection->createSearchIndex(
[
'fields' => [
[
'type' => 'autoEmbed',
'modality' => 'text',
'path' => 'description',
'model' => 'voyage-4-large',
'numDimensions' => 1024,
'quantization' => 'scalar',
'similarity' => 'dotProduct',
'indexingMethod' => 'hnsw',
'hnswOptions' => [
'maxEdges' => 32,
'numEdgeCandidates' => 200,
],
],
],
],
['name' => 'my_auto_embed_index', 'type' => 'vectorSearch'],
);
}
}
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