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Improve reference for fields parameter #34964

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30 changes: 18 additions & 12 deletions sdk/search/azure-search-documents/azure/search/documents/_generated/models/_models_py3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1983,8 +1983,9 @@ class VectorQuery(_serialization.Model):
:vartype kind: str or ~azure.search.documents.models.VectorQueryKind
:ivar k_nearest_neighbors: Number of nearest neighbors to return as top hits.
:vartype k_nearest_neighbors: int
:ivar fields: Vector Fields of type Collection(Edm.Single) to be included in the vector
searched.
:ivar fields: The comma-separated list of field names to be included in the vector search.
Each of the fields must be a valid vector type, such as Collection(Edm.Single). If multiple
fields are given, the vector will be used to find the closest matches across all fields.
:vartype fields: str
:ivar exhaustive: When true, triggers an exhaustive k-nearest neighbor search across all
vectors within the vector index. Useful for scenarios where exact matches are critical, such as
Expand Down Expand Up @@ -2023,8 +2024,9 @@ def __init__(
"""
:keyword k_nearest_neighbors: Number of nearest neighbors to return as top hits.
:paramtype k_nearest_neighbors: int
:keyword fields: Vector Fields of type Collection(Edm.Single) to be included in the vector
searched.
:keyword fields: The comma-separated list of field names to be included in the vector search.
Each of the fields must be a valid vector type, such as Collection(Edm.Single). If multiple
fields are given, the vector will be used to find the closest matches across all fields.
:paramtype fields: str
:keyword exhaustive: When true, triggers an exhaustive k-nearest neighbor search across all
vectors within the vector index. Useful for scenarios where exact matches are critical, such as
Expand Down Expand Up @@ -2055,8 +2057,9 @@ class VectorizableTextQuery(VectorQuery):
:vartype kind: str or ~azure.search.documents.models.VectorQueryKind
:ivar k_nearest_neighbors: Number of nearest neighbors to return as top hits.
:vartype k_nearest_neighbors: int
:ivar fields: Vector Fields of type Collection(Edm.Single) to be included in the vector
searched.
:ivar fields: The comma-separated list of field names to be included in the vector search.
Each of the fields must be a valid vector type, such as Collection(Edm.Single). If multiple
fields are given, the vector will be used to find the closest matches across all fields.
:vartype fields: str
:ivar exhaustive: When true, triggers an exhaustive k-nearest neighbor search across all
vectors within the vector index. Useful for scenarios where exact matches are critical, such as
Expand Down Expand Up @@ -2098,8 +2101,9 @@ def __init__(
"""
:keyword k_nearest_neighbors: Number of nearest neighbors to return as top hits.
:paramtype k_nearest_neighbors: int
:keyword fields: Vector Fields of type Collection(Edm.Single) to be included in the vector
searched.
:keyword fields: The comma-separated list of field names to be included in the vector search.
Each of the fields must be a valid vector type, such as Collection(Edm.Single). If multiple
fields are given, the vector will be used to find the closest matches across all fields.
:paramtype fields: str
:keyword exhaustive: When true, triggers an exhaustive k-nearest neighbor search across all
vectors within the vector index. Useful for scenarios where exact matches are critical, such as
Expand Down Expand Up @@ -2134,8 +2138,9 @@ class VectorizedQuery(VectorQuery):
:vartype kind: str or ~azure.search.documents.models.VectorQueryKind
:ivar k_nearest_neighbors: Number of nearest neighbors to return as top hits.
:vartype k_nearest_neighbors: int
:ivar fields: Vector Fields of type Collection(Edm.Single) to be included in the vector
searched.
:ivar fields: The comma-separated list of field names to be included in the vector search.
Each of the fields must be a valid vector type, such as Collection(Edm.Single). If multiple
fields are given, the vector will be used to find the closest matches across all fields.
:vartype fields: str
:ivar exhaustive: When true, triggers an exhaustive k-nearest neighbor search across all
vectors within the vector index. Useful for scenarios where exact matches are critical, such as
Expand Down Expand Up @@ -2177,8 +2182,9 @@ def __init__(
"""
:keyword k_nearest_neighbors: Number of nearest neighbors to return as top hits.
:paramtype k_nearest_neighbors: int
:keyword fields: Vector Fields of type Collection(Edm.Single) to be included in the vector
searched.
:keyword fields: The comma-separated list of field names to be included in the vector search.
Each of the fields must be a valid vector type, such as Collection(Edm.Single). If multiple
fields are given, the vector will be used to find the closest matches across all fields.
:paramtype fields: str
:keyword exhaustive: When true, triggers an exhaustive k-nearest neighbor search across all
vectors within the vector index. Useful for scenarios where exact matches are critical, such as
Expand Down