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amazon_opensearch_vector_store_driver

AmazonOpenSearchVectorStoreDriver

Bases: OpenSearchVectorStoreDriver

A Vector Store Driver for Amazon OpenSearch.

Attributes:

Name Type Description
session Session

The boto3 session to use.
service str

Service name for AWS Signature v4. Values can be 'es' or 'aoss' for for OpenSearch Serverless. Defaults to 'es'.
http_auth str | tuple[str, str]

The HTTP authentication credentials to use. Defaults to using credentials in the boto3 session.
client str | tuple[str, str]

An optional OpenSearch client to use. Defaults to a new client using the host, port, http_auth, use_ssl, and verify_certs attributes.
Source code in griptape/drivers/vector/amazon_opensearch_vector_store_driver.py 
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@define
class AmazonOpenSearchVectorStoreDriver(OpenSearchVectorStoreDriver):
    """A Vector Store Driver for Amazon OpenSearch.

    Attributes:
        session: The boto3 session to use.
        service: Service name for AWS Signature v4. Values can be 'es' or 'aoss' for for OpenSearch Serverless. Defaults to 'es'.
        http_auth: The HTTP authentication credentials to use. Defaults to using credentials in the boto3 session.
        client: An optional OpenSearch client to use. Defaults to a new client using the host, port, http_auth, use_ssl, and verify_certs attributes.
    """

    session: Session = field(default=Factory(lambda: import_optional_dependency("boto3").Session()), kw_only=True)
    service: str = field(default="es", kw_only=True)
    http_auth: str | tuple[str, str] = field(
        default=Factory(
            lambda self: import_optional_dependency("opensearchpy").AWSV4SignerAuth(
                self.session.get_credentials(),
                self.session.region_name,
                self.service,
            ),
            takes_self=True,
        ),
    )

    def upsert_vector(
        self,
        vector: list[float],
        *,
        vector_id: Optional[str] = None,
        namespace: Optional[str] = None,
        meta: Optional[dict] = None,
        **kwargs,
    ) -> str:
        """Inserts or updates a vector in OpenSearch.

        If a vector with the given vector ID already exists, it is updated; otherwise, a new vector is inserted.
        Metadata associated with the vector can also be provided.
        """
        vector_id = vector_id or str_to_hash(str(vector))
        doc = {"vector": vector, "namespace": namespace, "metadata": meta}
        doc.update(kwargs)
        if self.service == "aoss":
            response = self.client.index(index=self.index_name, body=doc)
        else:
            response = self.client.index(index=self.index_name, id=vector_id, body=doc)

        return response["_id"]

http_auth: str | tuple[str, str] = field(default=Factory(lambda self: import_optional_dependency('opensearchpy').AWSV4SignerAuth(self.session.get_credentials(), self.session.region_name, self.service), takes_self=True)) class-attribute instance-attribute

service: str = field(default='es', kw_only=True) class-attribute instance-attribute

session: Session = field(default=Factory(lambda: import_optional_dependency('boto3').Session()), kw_only=True) class-attribute instance-attribute

upsert_vector(vector, *, vector_id=None, namespace=None, meta=None, **kwargs)

Inserts or updates a vector in OpenSearch.

If a vector with the given vector ID already exists, it is updated; otherwise, a new vector is inserted. Metadata associated with the vector can also be provided.

Source code in griptape/drivers/vector/amazon_opensearch_vector_store_driver.py 
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def upsert_vector(
    self,
    vector: list[float],
    *,
    vector_id: Optional[str] = None,
    namespace: Optional[str] = None,
    meta: Optional[dict] = None,
    **kwargs,
) -> str:
    """Inserts or updates a vector in OpenSearch.

    If a vector with the given vector ID already exists, it is updated; otherwise, a new vector is inserted.
    Metadata associated with the vector can also be provided.
    """
    vector_id = vector_id or str_to_hash(str(vector))
    doc = {"vector": vector, "namespace": namespace, "metadata": meta}
    doc.update(kwargs)
    if self.service == "aoss":
        response = self.client.index(index=self.index_name, body=doc)
    else:
        response = self.client.index(index=self.index_name, id=vector_id, body=doc)

    return response["_id"]