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Terraform Bedrock Module

Amazon Bedrock is a fully managed service that offers a choice of foundation models (FMs) along with a broad set of capabilities for building generative AI applications.

This module includes resources to deploy Bedrock features.

Knowledge Bases

With Knowledge Bases for Amazon Bedrock, you can give FMs and agents contextual information from your company’s private data sources for Retrieval Augmented Generation (RAG) to deliver more relevant, accurate, and customized responses.

Create a Knowledge Base

A vector index on a vector store is required to create a Knowledge Base. This construct currently supports Amazon OpenSearch Serverless, Amazon RDS Aurora PostgreSQL, Pinecone, and MongoDB. By default, this resource will create an OpenSearch Serverless vector collection and index for each Knowledge Base you create, but you can provide an existing collection to have more control. For other resources you need to have the vector stores already created and credentials stored in AWS Secrets Manager.

The resource accepts an instruction prop that is provided to any Bedrock Agent it is associated with so the agent can decide when to query the Knowledge Base.

To create a knowledge base, make sure you pass in the appropriate variables and set the create_kb variable to true.

Example default Opensearch Serverless Agent with Knowledgebase

provider "opensearch" {
  url         = module.bedrock.default_collection[0].collection_endpoint
  healthcheck = false
}

module "bedrock" {
  source  = "aws-ia/bedrock/aws"
  version = "0.0.1"
  create_kb = true
  create_default_kb = true
  foundation_model = "anthropic.claude-v2"
  instruction = "You are an automotive assisant who can provide detailed information about cars to a customer."
}

Knowledge Base - Data Sources

Data sources are the various repositories or systems from which information is extracted and ingested into the knowledge base. These sources provide the raw content that will be processed, indexed, and made available for querying within the knowledge base system. Data sources can include various types of systems such as document management systems, databases, file storage systems, and content management platforms. Supported Data Sources include Amazon S3 buckets.

  • Amazon S3. You can either create a new data source by passing in the existing data source arn to the input variable kb_s3_data_source or create a new one by leaving that value as null when create_default_kb is set to true.

Agents

Enable generative AI applications to execute multistep tasks across company systems and data sources.

Create an Agent

The following example creates an Agent with a simple instruction and without any action groups or knowedlge bases.

module "bedrock" {
  source  = "aws-ia/bedrock/aws"
  version = "0.0.1"
  foundation_model = "anthropic.claude-v2"
  instruction = "You are an automotive assisant who can provide detailed information about cars to a customer."
}

To create an Agent with a default Knowledge Base you simply set create_kb and create_default_kb to true:

module "bedrock" {
  source  = "aws-ia/bedrock/aws"
  version = "0.0.1"
  create_kb = true
  create_default_kb = true
  foundation_model = "anthropic.claude-v2"
  instruction = "You are an automotive assisant who can provide detailed information about cars to a customer."
}

Action Groups

An action group defines functions your agent can call. The functions are Lambda functions. The action group uses an OpenAPI schema to tell the agent what your functions do and how to call them. You can configure an action group by passing in the appropriate input variables.

Prepare the Agent

The Agent constructs take an optional parameter shouldPrepareAgent to indicate that the Agent should be prepared after any updates to an agent, Knowledge Base association, or action group. This may increase the time to create and update those resources. By default, this value is true.

Prompt Overrides

Bedrock Agents allows you to customize the prompts and LLM configuration for its different steps. You can disable steps or create a new prompt template. Prompt templates can be inserted from plain text files.

Requirements

Name Version
terraform >= 1.0.7
aws ~>5.0
awscc >= 1.0.0
opensearch = 2.2.0
random >= 3.6.0
time ~> 0.6

Providers

Name Version
aws ~>5.0
awscc >= 1.0.0
opensearch = 2.2.0
random >= 3.6.0
time ~> 0.6

Modules

No modules.

Resources

Name Type
aws_bedrockagent_data_source.knowledge_base_ds resource
aws_iam_policy.bedrock_knowledge_base_policy resource
aws_iam_role.agent_role resource
aws_iam_role.bedrock_knowledge_base_role resource
aws_iam_role_policy.agent_policy resource
aws_iam_role_policy.bedrock_kb_oss resource
aws_iam_role_policy.kb_policy resource
aws_iam_role_policy_attachment.bedrock_knowledge_base_policy_attachment resource
aws_opensearchserverless_access_policy.data_policy resource
aws_opensearchserverless_security_policy.nw_policy resource
aws_opensearchserverless_security_policy.security_policy resource
awscc_bedrock_agent.bedrock_agent resource
awscc_bedrock_knowledge_base.knowledge_base_default resource
awscc_bedrock_knowledge_base.knowledge_base_mongo resource
awscc_bedrock_knowledge_base.knowledge_base_opensearch resource
awscc_bedrock_knowledge_base.knowledge_base_pinecone resource
awscc_bedrock_knowledge_base.knowledge_base_rds resource
awscc_opensearchserverless_collection.default_collection resource
awscc_s3_bucket.s3_data_source resource
opensearch_index.default_oss_index resource
random_string.solution_prefix resource
time_sleep.wait_before_index_creation resource
aws_caller_identity.current data source
aws_iam_policy_document.agent_permissions data source
aws_iam_policy_document.agent_trust data source
aws_iam_policy_document.knowledge_base_permissions data source
aws_partition.current data source
aws_region.current data source

Inputs

Name Description Type Default Required
foundation_model The foundation model for the Bedrock agent. string n/a yes
instruction A narrative instruction to provide the agent as context. string n/a yes
action_group_description Description of the action group. string null no
action_group_name Name of the action group. string null no
action_group_state State of the action group. string null no
agent_description A description of agent. string null no
agent_name The name of your agent. string "TerraformBedrockAgents" no
api_schema_payload String OpenAPI Payload. string null no
api_schema_s3_bucket_name A bucket in S3. string null no
api_schema_s3_object_key An object key in S3. string null no
base_prompt_template Defines the prompt template with which to replace the default prompt template. string null no
collection_arn The ARN of the collection. string null no
collection_name The name of the collection. string null no
connection_string The endpoint URL for your index management page. string null no
create_ag Whether or not to create an action group. bool false no
create_agent Whether or not to deploy an agent. bool true no
create_default_kb Whether or not to create the default knowledge base. bool false no
create_kb Whether or not to attach a knowledge base. bool false no
create_mongo_config Whether or not to use MongoDB Atlas configuration bool false no
create_opensearch_config Whether or not to use Opensearch Serverless configuration bool false no
create_pinecone_config Whether or not to use Pinecone configuration bool false no
create_rds_config Whether or not to use RDS configuration bool false no
credentials_secret_arn The ARN of the secret in Secrets Manager that is linked to your database string null no
custom_control Custom control of action execution. string null no
database_name Name of the database. string null no
endpoint Database endpoint string null no
endpoint_service_name MongoDB Atlas endpoint service name. string null no
existing_kb The ID of the existing knowledge base. string null no
function_description Description of function. string null no
function_name Name for a resource. string null no
function_parameters_description Description of function parameter. string null no
function_parameters_required If a parameter is required for a function call. bool false no
function_parameters_type Parameter type. string null no
idle_session_ttl How long sessions should be kept open for the agent. number 600 no
kb_description Description of knowledge base. string "Terraform deployed Knowledge Base" no
kb_embedding_model_arn The ARN of the model used to create vector embeddings for the knowledge base. string "arn:aws:bedrock:us-east-1::foundation-model/amazon.titan-embed-text-v1" no
kb_name Name of the knowledge base. string "knowledge-base" no
kb_role_arn The ARN of the IAM role with permission to invoke API operations on the knowledge base. string null no
kb_s3_data_source The S3 data source ARN for the knowledge base. string null no
kb_state State of knowledge base; whether it is enabled or disabled string "ENABLED" no
kb_storage_type The storage type of a knowledge base. string null no
kb_tags A map of tags keys and values for the knowledge base. map(string) null no
kb_type The type of a knowledge base. string null no
kms_key_arn KMS encryption key to use for the agent. string null no
lambda_action_group_executor ARN of Lambda. string null no
max_length The maximum number of tokens to generate in the response. number 0 no
metadata_field The name of the field in which Amazon Bedrock stores metadata about the vector store. string "AMAZON_BEDROCK_METADATA" no
name_prefix This value is appended at the beginning of resource names. string "BedrockAgents" no
namespace The namespace to be used to write new data to your pinecone database string null no
override_lambda_arn The ARN of the Lambda function to use when parsing the raw foundation model output in parts of the agent sequence. string null no
parent_action_group_signature Action group signature for a builtin action. string null no
parser_mode Specifies whether to override the default parser Lambda function. string null no
primary_key_field The name of the field in which Bedrock stores the ID for each entry. string null no
prompt_creation_mode Specifies whether to override the default prompt template. string null no
prompt_override Whether to provide prompt override configuration. bool false no
prompt_state Specifies whether to allow the agent to carry out the step specified in the promptType. string null no
prompt_type The step in the agent sequence that this prompt configuration applies to. string null no
resource_arn The ARN of the vector store. string null no
skip_resource_in_use Specifies whether to allow deleting action group while it is in use. bool null no
stop_sequences A list of stop sequences. list(string) [] no
table_name The name of the table in the database. string null no
tags Tag bedrock agent resource. map(string) null no
temperature The likelihood of the model selecting higher-probability options while generating a response. number 0 no
text_field The name of the field in which Amazon Bedrock stores the raw text from your data. string "AMAZON_BEDROCK_TEXT_CHUNK" no
top_k Sample from the k most likely next tokens. number 50 no
top_p Cumulative probability cutoff for token selection. number 0.5 no
vector_field The name of the field where the vector embeddings are stored string "bedrock-knowledge-base-default-vector" no
vector_index_name The name of the vector index. string "bedrock-knowledge-base-default-index" no

Outputs

Name Description
default_collection Opensearch default collection value.