Awso_bedrock_agent.ValuesSourceval structure_to_value_aux :
('a * 'b option) list ->
f:(('a * 'b) list -> 'c) ->
[> `Structure of 'c ]val structure_to_wrapped_value :
wrapper:'a ->
response:'a ->
('b * 'c option) list ->
[> `Structure of ('a * [> `Structure of ('b * 'c) list ]) list ]The identifier information for an Amazon S3 bucket.
Contains details about the OpenAPI schema for the action group. For more information, see Action group OpenAPI schemas. You can either include the schema directly in the payload field or you can upload it to an S3 bucket and specify the S3 bucket location in the s3 field.
The request is denied because of missing access permissions.
Contains details about the Lambda function containing the business logic that is carried out upon invoking the action or the custom control method for handling the information elicited from the user.
Contains details about an action group.
Contains inference parameters to use when the agent invokes a foundation model in the part of the agent sequence defined by the promptType. For more information, see Inference parameters for foundation models.
Contains configurations to override a prompt template in one part of an agent sequence. For more information, see Advanced prompts.
Contains configurations to override prompts in different parts of an agent sequence. For more information, see Advanced prompts.
Configuration for SESSION_SUMMARY memory type enabled for the agent.
Details of the memory configuration.
Details about a guardrail associated with a resource.
Contains details about the Lambda function containing the orchestration logic carried out upon invoking the custom orchestration.
Details of custom orchestration.
Contains details about a parameter in a function for an action group. This data type is used in the following API operations: CreateAgentActionGroup request CreateAgentActionGroup response UpdateAgentActionGroup request UpdateAgentActionGroup response GetAgentActionGroup response
Defines parameters that the agent needs to invoke from the user to complete the function. Corresponds to an action in an action group. This data type is used in the following API operations: CreateAgentActionGroup request CreateAgentActionGroup response UpdateAgentActionGroup request UpdateAgentActionGroup response GetAgentActionGroup response
Defines functions that each define parameters that the agent needs to invoke from the user. Each function represents an action in an action group. This data type is used in the following API operations: CreateAgentActionGroup request CreateAgentActionGroup response UpdateAgentActionGroup request UpdateAgentActionGroup response GetAgentActionGroup response
Contains details about an action group.
Contains details about the routing configuration of the alias.
Contains details about the history of the alias.
Contains details about an alias of an agent.
Contains details about an alias of an agent.
An agent descriptor.
An agent collaborator.
An agent collaborator summary.
Defines an agent node in your flow. You specify the agent to invoke at this point in the flow. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
Contains details about a knowledge base that is associated with an agent.
Contains details about a knowledge base associated with an agent.
Contains details about an agent.
Contains details about a version of an agent.
Contains details about a version of an agent.
Defines tools, at least one of which must be requested by the model. No text is generated but the results of tool use are sent back to the model to help generate a response. For more information, see Use a tool to complete an Amazon Bedrock model response.
Makes an agent a collaborator for another agent.
Stores information about a field passed inside a request that resulted in an validation error.
Input validation failed. Check your request parameters and retry the request.
The number of requests exceeds the limit. Resubmit your request later.
The number of requests exceeds the service quota. Resubmit your request later.
The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.
An internal server error occurred. Retry your request.
There was a conflict performing an operation.
Makes an agent a collaborator for another agent.
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.
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.
Configuration for segmenting audio content during multimodal knowledge base ingestion. Determines how audio files are divided into chunks for processing.
Configuration settings for processing audio content in multimodal knowledge bases.
Defines tools. The model automatically decides whether to call a tool or to generate text instead. For more information, see Use a tool to complete an Amazon Bedrock model response.
Contains configurations for using Amazon Bedrock Data Automation as the parser for ingesting your data sources.
Configuration for segmenting video content during multimodal knowledge base ingestion. Determines how video files are divided into chunks for processing.
Configuration settings for processing video content in multimodal knowledge bases.
The vector configuration details for the Bedrock embeddings model.
Instructions for interpreting the contents of a document.
Settings for a foundation model used to parse documents for a data source.
The strategy used for performing context enrichment.
Context enrichment configuration is used to provide additional context to the RAG application using Amazon Bedrock foundation models.
Contains information about content defined inline in bytes.
Indicates where a cache checkpoint is located. All information before this checkpoint is cached to be accessed on subsequent requests.
The input schema for the tool. For more information, see Use a tool to complete an Amazon Bedrock model response.
Contains a specification for a tool. For more information, see Use a tool to complete an Amazon Bedrock model response.
Contains configurations for a tool that a model can use when generating a response. For more information, see Use a tool to complete an Amazon Bedrock model response.
Defines a specific tool that the model must request. No text is generated but the results of tool use are sent back to the model to help generate a response. For more information, see Use a tool to complete an Amazon Bedrock model response.
Defines which tools the model should request when invoked. For more information, see Use a tool to complete an Amazon Bedrock model response.
Configuration information for the tools that the model can use when generating a response. For more information, see Use a tool to complete an Amazon Bedrock model response.
Contains a system prompt to provide context to the model or to describe how it should behave. For more information, see Create a prompt using Prompt management.
Contains information about a variable in the prompt.
Contains the content for the message you pass to, or receive from a model. For more information, see Create a prompt using Prompt management.
A message input or response from a model. For more information, see Create a prompt using Prompt management.
Contains configurations to use a prompt in a conversational format. For more information, see Create a prompt using Prompt management.
Settings for semantic document chunking for a data source. Semantic chunking splits a document into into smaller documents based on groups of similar content derived from the text with natural language processing. With semantic chunking, each sentence is compared to the next to determine how similar they are. You specify a threshold in the form of a percentile, where adjacent sentences that are less similar than that percentage of sentence pairs are divided into separate chunks. For example, if you set the threshold to 90, then the 10 percent of sentence pairs that are least similar are split. So if you have 101 sentences, 100 sentence pairs are compared, and the 10 with the least similarity are split, creating 11 chunks. These chunks are further split if they exceed the max token size. You must also specify a buffer size, which determines whether sentences are compared in isolation, or within a moving context window that includes the previous and following sentence. For example, if you set the buffer size to 1, the embedding for sentence 10 is derived from sentences 9, 10, and 11 combined.
Token settings for a layer in a hierarchical chunking configuration.
Settings for hierarchical document chunking for a data source. Hierarchical chunking splits documents into layers of chunks where the first layer contains large chunks, and the second layer contains smaller chunks derived from the first layer. You configure the number of tokens to overlap, or repeat across adjacent chunks. For example, if you set overlap tokens to 60, the last 60 tokens in the first chunk are also included at the beginning of the second chunk. For each layer, you must also configure the maximum number of tokens in a chunk.
Configurations for when you choose fixed-size chunking. If you set the chunkingStrategy as NONE, exclude this field.
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.
Defines a collector node in your flow. This node takes an iteration of inputs and consolidates them into an array in the output. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
Defines a condition in the condition node.
Defines a condition node in your flow. You can specify conditions that determine which node comes next in the flow. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
The specific filters applied to your data source content. You can filter out or include certain content.
The configuration of filtering certain objects or content types of the data source.
The configuration of filtering the data source content. For example, configuring regular expression patterns to include or exclude certain content.
The configuration of the Confluence content. For example, configuring specific types of Confluence content.
The endpoint information to connect to your Confluence data source.
The configuration information to connect to Confluence as your data source.
Context enrichment configuration is used to provide additional context to the RAG application.
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.
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.
Creates an alias of an agent that can be used to deploy the agent.
Creates an alias of an agent that can be used to deploy the agent.
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.
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.
Settings for parsing document contents. If you exclude this field, the default parser converts the contents of each document into text before splitting it into chunks. Specify the parsing strategy to use in the parsingStrategy field and include the relevant configuration, or omit it to use the Amazon Bedrock default parser. For more information, see Parsing options for your data source. If you specify BEDROCK_DATA_AUTOMATION or BEDROCK_FOUNDATION_MODEL and it fails to parse a file, the Amazon Bedrock default parser will be used instead.
A Lambda function that processes documents.
A Lambda function that processes documents.
A custom processing step for documents moving through a data source ingestion pipeline. To process documents after they have been converted into chunks, set the step to apply to POST_CHUNKING.
An Amazon S3 location.
A location for storing content from data sources temporarily as it is processed by custom components in the ingestion pipeline.
Settings for customizing steps in the data source content ingestion pipeline. You can configure the data source to process documents with a Lambda function after they are parsed and converted into chunks. When you add a post-chunking transformation, the service stores chunked documents in an S3 bucket and invokes a Lambda function to process them. To process chunked documents with a Lambda function, define an S3 bucket path for input and output objects, and a transformation that specifies the Lambda function to invoke. You can use the Lambda function to customize how chunks are split, and the metadata for each chunk.
Contains details about how to ingest the documents in a data source.
Contains the configuration for server-side encryption.
The seed or starting point URL. You should be authorized to crawl the URL.
The configuration of web URLs that you want to crawl. You should be authorized to crawl the URLs.
The configuration of the URL/URLs for the web content that you want to crawl. You should be authorized to crawl the URLs.
The rate limits for the URLs that you want to crawl. You should be authorized to crawl the URLs.
The configuration of web URLs that you want to crawl. You should be authorized to crawl the URLs.
The configuration details for the web data source.
The endpoint information to connect to your SharePoint data source.
The configuration of the SharePoint content. For example, configuring specific types of SharePoint content.
The configuration information to connect to SharePoint as your data source.
The endpoint information to connect to your Salesforce data source.
The configuration of the Salesforce content. For example, configuring specific types of Salesforce content.
The configuration information to connect to Salesforce as your data source.
The configuration information to connect to Amazon S3 as your data source.
The connection configuration for the data source.
Connects a knowledge base to a data source. You specify the configuration for the specific data source service in the dataSourceConfiguration field. You can't change the chunkingConfiguration after you create the data source connector.
Contains details about a data source.
Connects a knowledge base to a data source. You specify the configuration for the specific data source service in the dataSourceConfiguration field. You can't change the chunkingConfiguration after you create the data source connector.
Contains information about a version that the alias maps to.
Determines how multiple nodes in a flow can run in parallel. Running nodes concurrently can improve your flow's performance.
Creates an alias of a flow for deployment. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Creates an alias of a flow for deployment. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Contains configurations for an output from a node.
Contains configurations for an input in an Amazon Bedrock Flows node.
Contains configurations for the Amazon S3 location in which to store the input into the node.
Contains configurations for the service to use for storing the input into the node.
Contains configurations for a Storage node in a flow. This node stores the input in an Amazon S3 location that you specify.
Contains configurations for the Amazon S3 location from which to retrieve data to return as the output from the node.
Contains configurations for the service to use for retrieving data to return as the output from the node.
Contains configurations for a Retrieval node in a flow. This node retrieves data from the Amazon S3 location that you specify and returns it as the output.
Contains configurations for a prompt from Prompt management to use in a node.
Contains configurations for a text prompt template. To include a variable, enclose a word in double curly braces as in {{variable}}.
Contains the message for a prompt. For more information, see Construct and store reusable prompts with Prompt management in Amazon Bedrock.
Contains inference configurations related to model inference for a prompt. For more information, see Inference parameters.
Contains inference configurations for the prompt.
Contains configurations for a prompt defined inline in the node.
Contains configurations for a prompt and whether it is from Prompt management or defined inline.
Contains configurations for a prompt node in the flow. You can use a prompt from Prompt management or you can define one in this node. If the prompt contains variables, the inputs into this node will fill in the variables. The output from this node is the response generated by the model. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
Contains configurations for an output flow node in the flow. You specify the data type expected for the input into the node in the type field and how to return the final output in the expression field.
Contains configurations for the input node of a DoWhile loop in the flow.
Contains configurations for the controller node of a DoWhile loop in the flow.
Contains configurations for a Lex node in the flow. You specify a Amazon Lex bot to invoke. This node takes an utterance as the input and returns as the output the intent identified by the Amazon Lex bot. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
Contains configurations for a Lambda function node in the flow. You specify the Lambda function to invoke and the inputs into the function. The output is the response that is defined in the Lambda function. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
Configures the Amazon Bedrock model used for reranking retrieved results.
Specifies a metadata field to include or exclude during the reranking process.
Configures the metadata fields to include or exclude during the reranking process when using selective mode.
Specifies how metadata fields should be handled during the reranking process.
Configures the Amazon Bedrock reranker model to improve the relevance of retrieved results.
Specifies how retrieved results from a knowledge base are reranked to improve relevance.
Defines a custom prompt template for orchestrating the retrieval and generation process.
The performance-related configuration options for the knowledge base retrieval and generation process.
Configures how the knowledge base orchestrates the retrieval and generation process, allowing for customization of prompts, inference parameters, and performance settings.
Contains configurations for a knowledge base node in a flow. This node takes a query as the input and returns, as the output, the retrieved responses directly (as an array) or a response generated based on the retrieved responses. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
Contains configurations for an iterator node in a flow. Takes an input that is an array and iteratively sends each item of the array as an output to the following node. The size of the array is also returned in the output. The output flow node at the end of the flow iteration will return a response for each member of the array. To return only one response, you can include a collector node downstream from the iterator node.
Contains configurations for the input flow node for a flow. This node takes the input from flow invocation and passes it to the next node in the data type that you specify.
Contains configurations for an inline code node in your flow. Inline code nodes let you write and execute code directly within your flow, enabling data transformations, custom logic, and integrations without needing an external Lambda function.
The configuration of a connection originating from a node that isn't a Condition node.
The configuration of a connection between a condition node and another node.
The configuration of the connection.
Contains information about a connection between two nodes in the flow.
module FlowDefinition : sig ... endThe definition of the nodes and connections between nodes in the flow.
module FlowNode : sig ... endContains configurations about a node in the flow.
module FlowNodeConfiguration : sig ... endContains configurations for a node in your flow. For more information, see Node types in a flow in the Amazon Bedrock User Guide.
module FlowNodes : sig ... endmodule LoopFlowNodeConfiguration : sig ... endContains configurations for the nodes of a DoWhile loop in your flow. A DoWhile loop is made up of the following nodes: Loop - The container node that holds the loop's flow definition. This node encompasses the entire loop structure. LoopInput - The entry point node for the loop. This node receives inputs from nodes outside the loop and from previous loop iterations. Body nodes - The processing nodes that execute within each loop iteration. These can be nodes for handling data in your flow, such as a prompt or Lambda function nodes. Some node types aren't supported inside a DoWhile loop body. For more information, see LoopIncompatibleNodeTypeFlowValidationDetails. LoopController - The node that evaluates whether the loop should continue or exit based on a condition. These nodes work together to create a loop that runs at least once and continues until a specified condition is met or a maximum number of iterations is reached.
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.
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.
Creates a version of the flow that you can deploy. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Creates a version of the flow that you can deploy. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Contains the storage configuration of the knowledge base for S3 vectors.
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 Redis Enterprise Cloud. For more information, see Create a vector index in Redis Enterprise Cloud.
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.
Contains details about the storage configuration of the knowledge base in Pinecone. For more information, see Create a vector index 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 OpenSearch Service. For more information, see Create a vector index in Amazon OpenSearch Service.
Contains the names of the fields to which to map information about the vector store.
Contains details about the Managed Cluster configuration of the knowledge base in Amazon OpenSearch Service. For more information, see Create a vector index in OpenSearch Managed Cluster.
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 Neptune Analytics. For more information, see Create a vector index in Amazon Neptune Analytics.
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 MongoDB Atlas.
Contains the storage configuration of the knowledge base.
Contains information about a storage location for images extracted from multimodal documents in your data source.
Specifies configurations for the storage location of the images extracted from multimodal documents in your data source. These images can be retrieved and returned to the end user.
The configuration details for the embeddings model.
Contains details about the model used to create vector embeddings for the knowledge base.
Contains configurations for storage in Amazon Redshift.
Contains configurations for storage in Glue Data Catalog.
Contains configurations for Amazon Redshift data storage. Specify the data storage service to use in the type field and include the corresponding field. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.
Specifies configurations for authentication to a Redshift Serverless. Specify the type of authentication to use in the type field and include the corresponding field. If you specify IAM authentication, you don't need to include another field.
Contains configurations for authentication to Amazon Redshift Serverless.
Contains configurations for authentication to an Amazon Redshift provisioned data warehouse. Specify the type of authentication to use in the type field and include the corresponding field. If you specify IAM authentication, you don't need to include another field.
Contains configurations for a provisioned Amazon Redshift query engine.
Contains configurations for an Amazon Redshift query engine. Specify the type of query engine in type and include the corresponding field. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.
Contains information about a column in the current table for the query engine to consider.
Contains information about a table for the query engine to consider.
Contains configurations for a query, each of which defines information about example queries to help the query engine generate appropriate SQL queries.
>Contains configurations for context to use during query generation.
Contains configurations for query generation. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide..
Contains configurations for an Amazon Redshift database. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.
Contains configurations for a knowledge base connected to an SQL database. Specify the SQL database type in the type field and include the corresponding field. For more information, see Build a knowledge base by connecting to a structured data source in the Amazon Bedrock User Guide.
Settings for an Amazon Kendra knowledge base.
Contains details about the vector embeddings configuration of the knowledge base.
Creates a knowledge base. A knowledge base contains your data sources so that Large Language Models (LLMs) can use your data. 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 a knowledge base. 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.
Contains information about a knowledge base.
Creates a knowledge base. A knowledge base contains your data sources so that Large Language Models (LLMs) can use your data. 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 a knowledge base. 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.
Contains a key-value pair that defines a metadata tag and value to attach to a prompt variant. For more information, see Create a prompt using Prompt management.
Contains specifications for an Amazon Bedrock agent with which to use the prompt. For more information, see Create a prompt using Prompt management and Automate tasks in your application using conversational agents.
Contains specifications for a generative AI resource with which to use the prompt. For more information, see Create a prompt using Prompt management.
Contains details about a variant of the prompt.
Creates a prompt in your prompt library that you can add to a flow. For more information, see Prompt management in Amazon Bedrock, Create a prompt using Prompt management and Prompt flows in Amazon Bedrock in the Amazon Bedrock User Guide.
Creates a prompt in your prompt library that you can add to a flow. For more information, see Prompt management in Amazon Bedrock, Create a prompt using Prompt management and Prompt flows in Amazon Bedrock in the Amazon Bedrock User Guide.
Creates a static snapshot of your prompt that can be deployed to production. For more information, see Deploy prompts using Prompt management by creating versions in the Amazon Bedrock User Guide.
Creates a static snapshot of your prompt that can be deployed to production. For more information, see Deploy prompts using Prompt management by creating versions in the Amazon Bedrock User Guide.
Contains information about content defined inline in text.
Contains information about content defined inline to ingest into a data source. Choose a type and include the field that corresponds to it.
Contains information about the Amazon S3 location of the file containing the content to ingest into a knowledge base connected to a custom data source.
Contains information about the identifier of the document to ingest into a custom data source.
Contains information about the content to ingest into a knowledge base connected to a custom data source. Choose a sourceType and include the field that corresponds to it.
Details about a cyclic connection detected in the flow.
Contains details about a data source.
Deletes an action group in an agent.
Deletes an action group in an agent.
Deletes an alias of an agent.
Deletes an alias of an agent.
Deletes an agent.
Deletes an agent.
Deletes a version of an agent.
Deletes a version of an agent.
Deletes a data source from a knowledge base.
Deletes a data source from a knowledge base.
Deletes an alias of a flow.
Deletes an alias of a flow.
Deletes a flow.
Deletes a flow.
Deletes a version of a flow.
Deletes a version of a flow.
Contains information that identifies the document.
Deletes documents from a data source and syncs the changes to the knowledge base that is connected to it. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
Contains the details for a document that was ingested or deleted.
Deletes documents from a data source and syncs the changes to the knowledge base that is connected to it. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
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.
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.
Deletes a prompt or a version of it, depending on whether you include the promptVersion field or not. For more information, see Delete prompts from the Prompt management tool and Delete a version of a prompt from the Prompt management tool in the Amazon Bedrock User Guide.
Deletes a prompt or a version of it, depending on whether you include the promptVersion field or not. For more information, see Delete prompts from the Prompt management tool and Delete a version of a prompt from the Prompt management tool in the Amazon Bedrock User Guide.
Disassociates an agent collaborator.
Disassociates an agent collaborator.
Disassociates a knowledge base from an agent.
Disassociates a knowledge base from an agent.
Contains information about the content to ingest into a knowledge base connected to an Amazon S3 data source.
Contains information about the content of a document. Choose a dataSourceType and include the field that corresponds to it.
Contains the value of the metadata attribute. Choose a type and include the field that corresponds to it.
Contains information about a metadata attribute.
Contains information about the metadata associate with the content to ingest into a knowledge base. Choose a type and include the field that corresponds to it.
Details about duplicate condition expressions found in a condition node.
Details about duplicate connections found between two nodes in the flow.
Contains information about an alias of a flow. This data type is used in the following API operations: ListFlowAliases response
Contains the definition of a flow.
Details about an unspecified validation that doesn't fit other categories.
Details about unsatisfied conditions for a connection. A condition is unsatisfied if it can never be true, for example two branches of condition node cannot be simultaneously true.
Details about an unreachable node in the flow. A node is unreachable when there are no paths to it from any starting node.
Details about an unknown output for a node.
Details about an unknown input for a node.
Details about an unknown target input for a connection.
Details about an unknown target node for a connection.
Details about an unknown source output for a connection.
Details about an unknown source node for a connection.
Details about an unknown condition for a connection.
Details about an unfulfilled node input with no valid connections.
Details about multiple connections to a single node input.
Details about a flow that contains multiple LoopInput nodes in a DoWhile loop.
Details about a flow that contains multiple LoopController nodes in a DoWhile loop.
Details about missing starting nodes (such as FlowInputNode) in the flow.
Details about a missing required output in a node.
Details about a missing required input in a node.
Details about a node missing a required configuration.
Details about a flow that's missing a required LoopInput node in a DoWhile loop.
Details about a flow that's missing a required LoopController node in a DoWhile loop.
Details about missing ending nodes (such as FlowOutputNode) in the flow.
Details about a missing default condition in a conditional node.
Details about a connection missing required configuration.
Details about mismatched output data types in a node.
Details about mismatched input data types in a node.
Details about a malformed input expression in a node.
Details about a malformed condition expression in a node.
Details about a flow that contains an incompatible node in a DoWhile loop.
Details about a flow that contains connections that violate loop boundary rules.
Details about incompatible data types in a connection between nodes.
A union type containing various possible validation issues in the flow.
Contains information about validation of the flow. This data type is used in the following API operations: GetFlow response GetFlowVersion response
Contains information about a version of a flow. This data type is used in the following API operations: ListFlowVersions response
Gets information about an action group for an agent.
Gets information about an action group for an agent.
Gets information about an alias of an agent.
Gets information about an alias of an agent.
Retrieves information about an agent's collaborator.
Retrieves information about an agent's collaborator.
Gets information about a knowledge base associated with an agent.
Gets information about a knowledge base associated with an agent.
Gets information about an agent.
Gets information about an agent.
Gets details about a version of an agent.
Gets details about a version of an agent.
Gets information about a data source.
Gets information about a data source.
Retrieves information about a flow. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Retrieves information about a flow. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Retrieves information about a flow. For more information, see Manage a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Retrieves information about a flow. For more information, see Manage a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Retrieves information about a version of a flow. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Retrieves information about a version of a flow. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Gets information about a data ingestion job. Data sources are ingested into your knowledge base so that Large Language Models (LLMs) can use your data.
Contains the statistics for the data ingestion job.
Contains details about a data ingestion job. Data sources are ingested into a knowledge base so that Large Language Models (LLMs) can use your data. This data type is used in the following API operations: StartIngestionJob response GetIngestionJob response ListIngestionJob response
Gets information about a data ingestion job. Data sources are ingested into your knowledge base so that Large Language Models (LLMs) can use your data.
Retrieves specific documents from a data source that is connected to a knowledge base. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
Retrieves specific documents from a data source that is connected to a knowledge base. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
Gets information about a knowledge base.
Gets information about a knowledge base.
Retrieves information about the working draft (DRAFT version) of a prompt or a version of it, depending on whether you include the promptVersion field or not. For more information, see View information about prompts using Prompt management and View information about a version of your prompt in the Amazon Bedrock User Guide.
Retrieves information about the working draft (DRAFT version) of a prompt or a version of it, depending on whether you include the promptVersion field or not. For more information, see View information about prompts using Prompt management and View information about a version of your prompt in the Amazon Bedrock User Guide.
Contains information about a document to ingest into a knowledge base and metadata to associate with it.
Ingests documents directly into the knowledge base that is connected to the data source. The dataSourceType specified in the content for each document must match the type of the data source that you specify in the header. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
Ingests documents directly into the knowledge base that is connected to the data source. The dataSourceType specified in the content for each document must match the type of the data source that you specify in the header. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
The definition of a filter to filter the data.
The parameters of sorting the data.
Contains details about a data ingestion job.
Contains details about a knowledge base.
Lists the action groups for an agent and information about each one.
Lists the action groups for an agent and information about each one.
Lists the aliases of an agent and information about each one.
Lists the aliases of an agent and information about each one.
Retrieve a list of an agent's collaborators.
Retrieve a list of an agent's collaborators.
Lists knowledge bases associated with an agent and information about each one.
Lists knowledge bases associated with an agent and information about each one.
Lists the versions of an agent and information about each version.
Lists the versions of an agent and information about each version.
Lists the agents belonging to an account and information about each agent.
Lists the agents belonging to an account and information about each agent.
Lists the data sources in a knowledge base and information about each one.
Lists the data sources in a knowledge base and information about each one.
Returns a list of aliases for a flow.
Returns a list of aliases for a flow.
Returns a list of information about each flow. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Returns a list of information about each flow. For more information, see Deploy a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Returns a list of flows and information about each flow. For more information, see Manage a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Returns a list of flows and information about each flow. For more information, see Manage a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Lists the data ingestion jobs for a data source. The list also includes information about each job.
Lists the data ingestion jobs for a data source. The list also includes information about each job.
Retrieves all the documents contained in a data source that is connected to a knowledge base. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
Retrieves all the documents contained in a data source that is connected to a knowledge base. For more information, see Ingest changes directly into a knowledge base in the Amazon Bedrock User Guide.
Lists the knowledge bases in an account. The list also includesinformation about each knowledge base.
Lists the knowledge bases in an account. The list also includesinformation about each knowledge base.
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.
Contains information about a prompt in your Prompt management tool. This data type is used in the following API operations: ListPrompts response
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.
List all the tags for the resource you specify.
List all the tags for the resource you specify.
Creates a DRAFT version of the agent that can be used for internal testing.
Creates a DRAFT version of the agent that can be used for internal testing.
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.
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.
Begins a data ingestion job. Data sources are ingested into your knowledge base so that Large Language Models (LLMs) can use your data.
Begins a data ingestion job. Data sources are ingested into your knowledge base so that Large Language Models (LLMs) can use your data.
Stops a currently running data ingestion job. You can send a StartIngestionJob request again to ingest the rest of your data when you are ready.
Stops a currently running data ingestion job. You can send a StartIngestionJob request again to ingest the rest of your data when you are ready.
Associate tags with a resource. For more information, see Tagging resources in the Amazon Bedrock User Guide.
Associate tags with a resource. For more information, see Tagging resources in the Amazon Bedrock User Guide.
Remove tags from a resource.
Remove tags from a resource.
Updates the configuration for an action group for an agent.
Updates the configuration for an action group for an agent.
Updates configurations for an alias of an agent.
Updates configurations for an alias of an agent.
Updates an agent's collaborator.
Updates an agent's collaborator.
Updates the configuration for a knowledge base that has been associated with an agent.
Updates the configuration for a knowledge base that has been associated with an agent.
Updates the configuration of an agent.
Updates the configuration of an agent.
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.
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.
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.
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.
Modifies a flow. Include both fields that you want to keep and fields that you want to change. For more information, see How it works and Create a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
Modifies a flow. Include both fields that you want to keep and fields that you want to change. For more information, see How it works and Create a flow in Amazon Bedrock in the Amazon Bedrock User Guide.
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.
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.
Modifies a prompt in your prompt library. Include both fields that you want to keep and fields that you want to replace. For more information, see Prompt management in Amazon Bedrock and Edit prompts in your prompt library in the Amazon Bedrock User Guide.
Modifies a prompt in your prompt library. Include both fields that you want to keep and fields that you want to replace. For more information, see Prompt management in Amazon Bedrock and Edit prompts in your prompt library in the Amazon Bedrock User Guide.
Validates the definition of a flow.
Validates the definition of a flow.