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.