AWS Bedrock AI Agent

The AWS Bedrock deploy provider allows you to push versioned prompts and tools from Elacity directly into AWS Bedrock Agents. This integration automates the creation of agents, synchronization of Action Groups (tools), and handles the technical “Preparation” step required by Bedrock.

AWS Environment Setup (Step-by-Step)

Follow these steps to prepare your AWS account for integration with Elacity.

1. Create an IAM User

Elacity needs programmatic access to your AWS account to manage agents.

1. Log in to your AWS IAM Console.
2. Create a new user with a name like elacity-deployer.
3. Select Attach policies directly and add:
   • AmazonBedrockFullAccess
   • AWSLambda_FullAccess (required for tool execution)
4. Critical Step: Add iam:PassRole permission. Without this, you will get an AccessDeniedException during deployment. Create an Inline Policy for the user with the following JSON:

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   {
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       "Version": "2012-10-17",
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       "Statement": [
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           {
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               "Effect": "Allow",
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               "Action": "iam:PassRole",
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               "Resource": "*" 
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           }
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       ]
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   }
   (Note: You can replace * with the specific ARN of your Bedrock Service Role for better security).

2. Configure a Service Role for Bedrock

Bedrock Agents require a dedicated service role to interact with foundation models.

1. In the IAM Console, create a new Role.
2. Select AWS Service and then Bedrock.
3. Attach policies that grant access to the models you plan to use (e.g., Amazon Nova/Titan).
4. Important: Copy the Role ARN (e.g., arn:aws:iam::123456789012:role/BedrockAgentServiceRole). You will need this in Elacity.

3. Request Model Access

Navigate to the Bedrock Console in your target region and ensure you have “Granted” access to your chosen models (e.g., Amazon Nova/Titan, Meta Llama) under Model Access.

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Connection Setup in Elacity

1. Secret Configuration

In Elacity, navigate to Environments / Secrets and add your AWS credentials.

[!WARNING] Authentication Types:

• IAM User (Permanent Keys): Use AWS_ACCESS_KEY_ID (starts with AKIA) and AWS_SECRET_ACCESS_KEY. Leave AWS_SESSION_TOKEN empty.
• SSO / Temporary Credentials: Use AWS_ACCESS_KEY_ID (starts with ASIA), AWS_SECRET_ACCESS_KEY, and you MUST provide the AWS_SESSION_TOKEN.

2. Agent Configuration

When creating or updating an agent in Elacity, use the following provider-specific fields:

• Agent Name: The display name in the AWS console.
• Foundation Model: The exact model ID (e.g., amazon.nova-pro-v1:0).
• Agent Resource Role ARN: The ARN of the service role created in Step 2.
• Instruction: Your system prompt.

  [!IMPORTANT] Length Requirement: Bedrock agents require a substantial instruction. Elacity enforces a minimum of 40 characters for the cleaned instruction.

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Working with Tools (Action Groups)

AWS Bedrock uses Action Groups to represent tools. Elacity supports two main tool workflows:

Built-in AWS Tools

If you select a tool type like User Input, Elacity automatically configures it as a built-in Bedrock tool.

• System Name: AMAZON.UserInput
• Config: No Lambda or Schema required.

Custom Lambda Actions

For specialized logic, use the Lambda Action tool type.

1. Create a Lambda function in AWS.
2. Grant Bedrock permission to invoke it:

   $
   aws lambda add-permission --function-name YourFunctionName --principal bedrock.amazonaws.com --action lambda:InvokeFunction --statement-id AllowBedrock
3. Copy the Lambda ARN into the actionGroupExecutor field in the Elacity tool editor.
4. Schema: Provide either an API Schema (OpenAPI) or a Function Schema.

[!IMPORTANT] Conflict Rule: Do not provide both apiSchema and functionSchema in the same tool. Elacity will prioritize apiSchema if both are present.

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Troubleshooting & Typical Errors

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Deployment Verification

1. Click Deploy in Elacity.
2. Navigate to the AWS Bedrock Console > Agents.
3. Select your agent and verify the Action Groups are synced and the status is Prepared.