S3Vectors / Client / create_index
create_index¶
- S3Vectors.Client.create_index(**kwargs)¶
Note
Amazon S3 Vectors is in preview release for Amazon S3 and is subject to change.
Creates a vector index within a vector bucket. To specify the vector bucket, you must use either the vector bucket name or the vector bucket Amazon Resource Name (ARN).
Permissions
You must have the
s3vectors:CreateIndex
permission to use this operation.See also: AWS API Documentation
Request Syntax
response = client.create_index( vectorBucketName='string', vectorBucketArn='string', indexName='string', dataType='float32', dimension=123, distanceMetric='euclidean'|'cosine', metadataConfiguration={ 'nonFilterableMetadataKeys': [ 'string', ] } )
- Parameters:
vectorBucketName (string) – The name of the vector bucket to create the vector index in.
vectorBucketArn (string) – The Amazon Resource Name (ARN) of the vector bucket to create the vector index in.
indexName (string) –
[REQUIRED]
The name of the vector index to create.
dataType (string) –
[REQUIRED]
The data type of the vectors to be inserted into the vector index.
dimension (integer) –
[REQUIRED]
The dimensions of the vectors to be inserted into the vector index.
distanceMetric (string) –
[REQUIRED]
The distance metric to be used for similarity search.
metadataConfiguration (dict) –
The metadata configuration for the vector index.
nonFilterableMetadataKeys (list) – [REQUIRED]
Non-filterable metadata keys allow you to enrich vectors with additional context during storage and retrieval. Unlike default metadata keys, these keys can’t be used as query filters. Non-filterable metadata keys can be retrieved but can’t be searched, queried, or filtered. You can access non-filterable metadata keys of your vectors after finding the vectors. For more information about non-filterable metadata keys, see Vectors and Limitations and restrictions in the Amazon S3 User Guide.
(string) –
- Return type:
dict
- Returns:
Response Syntax
{}
Response Structure
(dict) –
Exceptions