Package-level declarations
Types
Contains the information of an Agent Action Group
Type of Executors for an Action Group
Type of Executors for an Action Group
History event for an alias for an Agent.
Details about the routing configuration for an Agent alias.
Contains information about the API Schema for the Action Group
Contains information about the API Schema for the Action Group
Function definition
Schema of Functions
Agent Knowledge Base
Parameter detail
BasePromptConfiguration per Prompt Type.
Configuration for prompt override.
The identifier for the S3 resource.
Details about how to chunk the documents in the data source. A chunk refers to an excerpt from a data source that is returned when the knowledge base that it belongs to is queried.
Specifies a raw data source location to ingest.
Configurations for when you choose fixed-size chunking. If you set the chunkingStrategy as NONE, exclude this field.
Contains information about the S3 configuration of the data source.
Contains details about the server-side encryption for the data source.
Details about how to chunk the documents in the data source. A chunk refers to an excerpt from a data source that is returned when the knowledge base that it belongs to is queried.
Content filter config in content policy.
Content policy config for a guardrail.
A managed words config.
Pii entity configuration.
A regex configuration.
Sensitive information policy config for a guardrail.
Topic config in topic policy.
Topic policy config for a guardrail.
A custom word config.
Word policy config for a guardrail.
Contains details about the embeddings model used for the knowledge base.
Contains the storage configuration of the knowledge base in Amazon OpenSearch Service.
A mapping of Bedrock Knowledge Base fields to OpenSearch Serverless field names
Contains the storage configuration of the knowledge base in Pinecone.
Contains the names of the fields to which to map information about the vector store.
Contains details about the storage configuration of the knowledge base in Amazon RDS. For more information, see Create a vector index in Amazon RDS.
Contains the names of the fields to which to map information about the vector store.
The vector store service in which the knowledge base is stored.
Contains details about the model used to create vector embeddings for the knowledge base.