AWS.BedrockAgent — AWS SDK for JavaScript (original) (raw)

Property Details

endpoint ⇒ AWS.Endpoint

Returns an Endpoint object representing the endpoint URL for service requests.

Method Details

associateAgentKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Associates a knowledge base with an agent. If a knowledge base is associated and its indexState is set to Enabled, the agent queries the knowledge base for information to augment its response to the user.

createAgent(params = {}, callback) ⇒ AWS.Request

Creates an agent that orchestrates interactions between foundation models, data sources, software applications, user conversations, and APIs to carry out tasks to help customers.

• Specify the following fields for security purposes.
  • agentResourceRoleArn – The Amazon Resource Name (ARN) of the role with permissions to invoke API operations on an agent.
  • (Optional) customerEncryptionKeyArn – The Amazon Resource Name (ARN) of a KMS key to encrypt the creation of the agent.
  • (Optional) idleSessionTTLinSeconds – Specify the number of seconds for which the agent should maintain session information. After this time expires, the subsequent InvokeAgent request begins a new session.
• To enable your agent to retain conversational context across multiple sessions, include a memoryConfiguration object. For more information, see Configure memory.
• To override the default prompt behavior for agent orchestration and to use advanced prompts, include a promptOverrideConfiguration object. For more information, see Advanced prompts.
• If your agent fails to be created, the response returns a list of failureReasons alongside a list of recommendedActions for you to troubleshoot.
• The agent instructions will not be honored if your agent has only one knowledge base, uses default prompts, has no action group, and user input is disabled.

createAgentActionGroup(params = {}, callback) ⇒ AWS.Request

Creates an action group for an agent. An action group represents the actions that an agent can carry out for the customer by defining the APIs that an agent can call and the logic for calling them.

To allow your agent to request the user for additional information when trying to complete a task, add an action group with the parentActionGroupSignature field set to AMAZON.UserInput.

To allow your agent to generate, run, and troubleshoot code when trying to complete a task, add an action group with the parentActionGroupSignature field set to AMAZON.CodeInterpreter.

You must leave the description, apiSchema, and actionGroupExecutor fields blank for this action group. During orchestration, if your agent determines that it needs to invoke an API in an action group, but doesn't have enough information to complete the API request, it will invoke this action group instead and return an Observation reprompting the user for more information.

createAgentAlias(params = {}, callback) ⇒ AWS.Request

Creates an alias of an agent that can be used to deploy the agent.

createDataSource(params = {}, callback) ⇒ AWS.Request

Creates a data source connector for a knowledge base.

You can't change the chunkingConfiguration after you create the data source connector.

createFlow(params = {}, callback) ⇒ AWS.Request

Creates a prompt flow that you can use to send an input through various steps to yield an output. Configure nodes, each of which corresponds to a step of the flow, and create connections between the nodes to create paths to different outputs. For more information, see How it works and Create a flow in Amazon Bedrock in the Amazon Bedrock User Guide.

createFlowAlias(params = {}, callback) ⇒ AWS.Request

createFlowVersion(params = {}, callback) ⇒ AWS.Request

createKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Creates a knowledge base that contains data sources from which information can be queried and used by LLMs. To create a knowledge base, you must first set up your data sources and configure a supported vector store. For more information, see Set up your data for ingestion.

Note: If you prefer to let Amazon Bedrock create and manage a vector store for you in Amazon OpenSearch Service, use the console. For more information, see Create a knowledge base.

• Provide the name and an optional description.
• Provide the Amazon Resource Name (ARN) with permissions to create a knowledge base in the roleArn field.
• Provide the embedding model to use in the embeddingModelArn field in the knowledgeBaseConfiguration object.
• Provide the configuration for your vector store in the storageConfiguration object.
  • For an Amazon OpenSearch Service database, use the opensearchServerlessConfiguration object. For more information, see Create a vector store in Amazon OpenSearch Service.
  • For an Amazon Aurora database, use the RdsConfiguration object. For more information, see Create a vector store in Amazon Aurora.
  • For a Pinecone database, use the pineconeConfiguration object. For more information, see Create a vector store in Pinecone.
  • For a Redis Enterprise Cloud database, use the redisEnterpriseCloudConfiguration object. For more information, see Create a vector store in Redis Enterprise Cloud.

createPromptVersion(params = {}, callback) ⇒ AWS.Request

deleteAgentActionGroup(params = {}, callback) ⇒ AWS.Request

Deletes an action group in an agent.

deleteAgentAlias(params = {}, callback) ⇒ AWS.Request

Deletes an alias of an agent.

deleteAgentVersion(params = {}, callback) ⇒ AWS.Request

Deletes a version of an agent.

deleteDataSource(params = {}, callback) ⇒ AWS.Request

Deletes a data source from a knowledge base.

deleteFlowAlias(params = {}, callback) ⇒ AWS.Request

Deletes an alias of a flow.

deleteFlowVersion(params = {}, callback) ⇒ AWS.Request

Deletes a version of a flow.

deleteKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Deletes a knowledge base. Before deleting a knowledge base, you should disassociate the knowledge base from any agents that it is associated with by making a DisassociateAgentKnowledgeBase request.

disassociateAgentKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Disassociates a knowledge base from an agent.

getAgent(params = {}, callback) ⇒ AWS.Request

Gets information about an agent.

getAgentActionGroup(params = {}, callback) ⇒ AWS.Request

Gets information about an action group for an agent.

getAgentAlias(params = {}, callback) ⇒ AWS.Request

Gets information about an alias of an agent.

getAgentKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Gets information about a knowledge base associated with an agent.

getAgentVersion(params = {}, callback) ⇒ AWS.Request

Gets details about a version of an agent.

getDataSource(params = {}, callback) ⇒ AWS.Request

Gets information about a data source.

getFlowVersion(params = {}, callback) ⇒ AWS.Request

getIngestionJob(params = {}, callback) ⇒ AWS.Request

Gets information about a ingestion job, in which a data source is added to a knowledge base.

getKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Gets information about a knoweldge base.

listAgentActionGroups(params = {}, callback) ⇒ AWS.Request

Lists the action groups for an agent and information about each one.

listAgentAliases(params = {}, callback) ⇒ AWS.Request

Lists the aliases of an agent and information about each one.

listAgentKnowledgeBases(params = {}, callback) ⇒ AWS.Request

Lists knowledge bases associated with an agent and information about each one.

listAgents(params = {}, callback) ⇒ AWS.Request

Lists the agents belonging to an account and information about each agent.

listAgentVersions(params = {}, callback) ⇒ AWS.Request

Lists the versions of an agent and information about each version.

listDataSources(params = {}, callback) ⇒ AWS.Request

Lists the data sources in a knowledge base and information about each one.

listFlowAliases(params = {}, callback) ⇒ AWS.Request

Returns a list of aliases for a flow.

listFlowVersions(params = {}, callback) ⇒ AWS.Request

listIngestionJobs(params = {}, callback) ⇒ AWS.Request

Lists the ingestion jobs for a data source and information about each of them.

listKnowledgeBases(params = {}, callback) ⇒ AWS.Request

Lists the knowledge bases in an account and information about each of them.

listPrompts(params = {}, callback) ⇒ AWS.Request

Returns either information about the working draft (DRAFT version) of each prompt in an account, or information about of all versions of a prompt, depending on whether you include the promptIdentifier field or not. For more information, see View information about prompts using Prompt management in the Amazon Bedrock User Guide.

listTagsForResource(params = {}, callback) ⇒ AWS.Request

List all the tags for the resource you specify.

prepareAgent(params = {}, callback) ⇒ AWS.Request

Creates a DRAFT version of the agent that can be used for internal testing.

prepareFlow(params = {}, callback) ⇒ AWS.Request

Prepares the DRAFT version of a flow so that it can be invoked. For more information, see Test a flow in Amazon Bedrock in the Amazon Bedrock User Guide.

startIngestionJob(params = {}, callback) ⇒ AWS.Request

Begins an ingestion job, in which a data source is added to a knowledge base.

tagResource(params = {}, callback) ⇒ AWS.Request

Associate tags with a resource. For more information, see Tagging resources in the Amazon Bedrock User Guide.

untagResource(params = {}, callback) ⇒ AWS.Request

Remove tags from a resource.

updateAgent(params = {}, callback) ⇒ AWS.Request

Updates the configuration of an agent.

updateAgentActionGroup(params = {}, callback) ⇒ AWS.Request

Updates the configuration for an action group for an agent.

updateAgentAlias(params = {}, callback) ⇒ AWS.Request

Updates configurations for an alias of an agent.

updateAgentKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Updates the configuration for a knowledge base that has been associated with an agent.

updateDataSource(params = {}, callback) ⇒ AWS.Request

Updates the configurations for a data source connector.

You can't change the chunkingConfiguration after you create the data source connector. Specify the existing chunkingConfiguration.

updateFlowAlias(params = {}, callback) ⇒ AWS.Request

Modifies the alias of a flow. Include both fields that you want to keep and ones that you want to change. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.

updateKnowledgeBase(params = {}, callback) ⇒ AWS.Request

Updates the configuration of a knowledge base with the fields that you specify. Because all fields will be overwritten, you must include the same values for fields that you want to keep the same.

You can change the following fields:

• name
• description
• roleArn

You can't change the knowledgeBaseConfiguration or storageConfiguration fields, so you must specify the same configurations as when you created the knowledge base. You can send a GetKnowledgeBase request and copy the same configurations.