Building domain-constrained AI agents with Bedrock Guardrails

import * as bedrock from 'aws-cdk-lib/aws-bedrock';

const guardrail = new bedrock.CfnGuardrail(this, 'TopicGuardrail', {
  name: `${config.prefix}-topic-guardrail`,
  blockedInputMessaging:
    'This query is outside the scope of the research platform. ' +
    'Please ask a research-related question.',
  blockedOutputsMessaging:
    'The response was filtered for content policy compliance.',
  topicPolicyConfig: {
    topicsConfig: [
      {
        name: 'Politics',
        type: 'DENY',
        definition: 'Political topics, elections, government policy',
      },
      {
        name: 'Entertainment',
        type: 'DENY',
        definition:
          'Movies, music, sports, celebrities, gaming',
      },
      {
        name: 'NonScience',
        type: 'DENY',
        definition:
          'Any topic not related to neuroscience, biology, or biomedical ' +
          'science including cooking, recipes, fashion, lifestyle, fitness, ' +
          'travel, finance',
      },
      {
        name: 'HomeAndDIY',
        type: 'DENY',
        definition:
          'Home repair, plumbing, electrical work, gardening, construction, ' +
          'DIY projects, household maintenance',
      },
    ],
  },
});


import {
  BedrockRuntimeClient,
  ApplyGuardrailCommand,
} from '@aws-sdk/client-bedrock-runtime';

const bedrockRuntime = new BedrockRuntimeClient({});

// Inside the Lambda handler, before agent invocation:
if (GUARDRAIL_ID) {
  const guardrailResult = await bedrockRuntime.send(
    new ApplyGuardrailCommand({
      guardrailIdentifier: GUARDRAIL_ID,
      guardrailVersion: GUARDRAIL_VERSION,
      source: 'INPUT',
      content: [{ text: { text: query } }],
    })
  );

  if (guardrailResult.action === 'GUARDRAIL_INTERVENED') {
    return {
      statusCode: 200,
      body: JSON.stringify({
        response:
          guardrailResult.outputs?.[0]?.text ||
          'Query outside scope.',
        blocked: true,
        sessionId,
      }),
    };
  }
}

// Query passed the guardrail, invoke the agent
const agentResponse = await agentCoreClient.send(
  new InvokeAgentRuntimeCommand({
    agentRuntimeArn: AGENT_RUNTIME_ARN,
    payload: JSON.stringify({ query, sessionId }),
  })
);


import * as iam from 'aws-cdk-lib/aws-iam';

chatLambda.addToRolePolicy(
  new iam.PolicyStatement({
    actions: ['bedrock:ApplyGuardrail'],
    resources: [
      `arn:aws:bedrock:${config.region}:${this.account}:guardrail/*`,
    ],
  })
);


const guardrail = new bedrock.CfnGuardrail(this, 'TopicGuardrail', {
  // ... topic policy config from above ...
  contentPolicyConfig: {
    filtersConfig: [
      {
        type: 'HATE',
        inputStrength: 'HIGH',
        outputStrength: 'HIGH',
      },
      {
        type: 'VIOLENCE',
        inputStrength: 'MEDIUM',
        outputStrength: 'MEDIUM',
      },
      {
        type: 'SEXUAL',
        inputStrength: 'HIGH',
        outputStrength: 'HIGH',
      },
    ],
  },
});