Struct CreateDataSourceInput

#[non_exhaustive]
pub struct CreateDataSourceInput {
    pub knowledge_base_id: Option<String>,
    pub client_token: Option<String>,
    pub name: Option<String>,
    pub description: Option<String>,
    pub data_source_configuration: Option<DataSourceConfiguration>,
    pub data_deletion_policy: Option<DataDeletionPolicy>,
    pub server_side_encryption_configuration: Option<ServerSideEncryptionConfiguration>,
    pub vector_ingestion_configuration: Option<VectorIngestionConfiguration>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

knowledge_base_id: Option<String>

The unique identifier of the knowledge base to which to add the data source.

client_token: Option<String>

A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency.

name: Option<String>

The name of the data source.

description: Option<String>

A description of the data source.

data_source_configuration: Option<DataSourceConfiguration>

The connection configuration for the data source.

data_deletion_policy: Option<DataDeletionPolicy>

The data deletion policy for the data source.

You can set the data deletion policy to:

• DELETE: Deletes all data from your data source that’s converted into vector embeddings upon deletion of a knowledge base or data source resource. Note that the vector store itself is not deleted, only the data. This flag is ignored if an Amazon Web Services account is deleted.

• RETAIN: Retains all data from your data source that’s converted into vector embeddings upon deletion of a knowledge base or data source resource. Note that the vector store itself is not deleted if you delete a knowledge base or data source resource.

server_side_encryption_configuration: Option<ServerSideEncryptionConfiguration>

Contains details about the server-side encryption for the data source.

vector_ingestion_configuration: Option<VectorIngestionConfiguration>

Contains details about how to ingest the documents in the data source.

Implementations

impl CreateDataSourceInput

pub fn knowledge_base_id(&self) -> Option<&str>

The unique identifier of the knowledge base to which to add the data source.

pub fn client_token(&self) -> Option<&str>

A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency.

pub fn name(&self) -> Option<&str>

The name of the data source.

pub fn description(&self) -> Option<&str>

A description of the data source.

pub fn data_source_configuration(&self) -> Option<&DataSourceConfiguration>

The connection configuration for the data source.

pub fn data_deletion_policy(&self) -> Option<&DataDeletionPolicy>

The data deletion policy for the data source.

You can set the data deletion policy to:

• DELETE: Deletes all data from your data source that’s converted into vector embeddings upon deletion of a knowledge base or data source resource. Note that the vector store itself is not deleted, only the data. This flag is ignored if an Amazon Web Services account is deleted.

• RETAIN: Retains all data from your data source that’s converted into vector embeddings upon deletion of a knowledge base or data source resource. Note that the vector store itself is not deleted if you delete a knowledge base or data source resource.

pub fn server_side_encryption_configuration( &self, ) -> Option<&ServerSideEncryptionConfiguration>

Contains details about the server-side encryption for the data source.

pub fn vector_ingestion_configuration( &self, ) -> Option<&VectorIngestionConfiguration>

Contains details about how to ingest the documents in the data source.

impl CreateDataSourceInput

pub fn builder() -> CreateDataSourceInputBuilder

Creates a new builder-style object to manufacture CreateDataSourceInput.

Trait Implementations

impl Clone for CreateDataSourceInput

fn clone(&self) -> CreateDataSourceInput

Returns a duplicate of the value.

const fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateDataSourceInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for CreateDataSourceInput

fn eq(&self, other: &CreateDataSourceInput) -> bool

Tests for self and other values to be equal, and is used by ==.

const fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateDataSourceInput