AWS S3 Vectors Engine

To use S3 Vectors as a Vector Engine, specify s3_vectors as the engine, and configure the associated location and AWS credentials.

datasets:
  - from: spice.ai:dataset.with.embeddings
    name: my_dataset
    vectors:
      enabled: true
      engine: s3_vectors
      params:
        s3_vectors_bucket: my-s3-vector-bucket
    columns:
      - name: "body"
        embeddings:
          - from: bedrock_titan

embeddings:
  - name: bedrock_titan
   # ... Define an embedding model to use.

Parameters

Parameter	Description	Example Value
`s3_vectors_arn`	The S3 vectors index to use. Incompatible with `s3_vectors_bucket` and `s3_vectors_index`.	`arn:aws:s3vectors:123456654321/bucket/a-bucket/index/index-of-important-embeddings`
`s3_vectors_aws_access_key_id`	The access key ID for the S3 vectors index	-
`s3_vectors_aws_region`	The AWS region for the S3 vectors index.	`us-east-1`
`s3_vectors_aws_secret_access_key`	The secret access key for the S3 vectors index	-
`s3_vectors_aws_session_token`	Session token for the S3 vectors index.	-
`s3_vectors_bucket`	The S3 vectors bucket to use. If `s3_vectors_index` is not specified, an index will be created based on the underlying embedding column. Incompatible with `s3_vectors_arn`	`a-bucket`
`s3_vectors_endpoint`	The endpoint for the S3 vectors index	`s3vectors.us-east-2.api.aws`
`s3_vectors_index`	The name of the s3 vectors index to use or create. Incompatible with `s3_vectors_arn`.	`index-of-important-embeddings`

Limitations

s3_vectors_index and s3_vectors_arn specify a single index for the dataset and therefore should not be used with a dataset containing more than one embedding column.

Parameters​

Parameters