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Update docstring
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django_mongodb_backend/expressions/search.py

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@@ -884,10 +884,11 @@ def as_mql(self, compiler, connection):
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class SearchVector(SearchExpression):
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"""
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Atlas Search expression that performs vector similarity search on embedded vectors.
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Atlas Search expression that performs vector similarity search using `$vectorSearch`.
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This expression uses the **knnBeta** operator to find documents whose vector
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embeddings are most similar to a given query vector.
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This expression uses the `$vectorSearch` stage to retrieve documents whose vector
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embeddings are most similar to a given query vector, according to approximate or
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exact nearest-neighbor search.
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Example:
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SearchVector("embedding", [0.1, 0.2, 0.3], limit=10, num_candidates=100)
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query_vector: The query vector to compare against.
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limit: Maximum number of matching documents to return.
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num_candidates: Optional number of candidates to consider during search.
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exact: Optional flag to enforce exact matching.
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exact: Optional flag to enforce exact matching (default is approximate).
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filter: Optional filter expression to narrow candidate documents.
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Reference: https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-stage/

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