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Web Services"},"license":"Apache-2.0","homepage":"https://github.com/aws/modern-data-architecture-accelerator#readme","repository":{"url":"git+https://github.com/aws/modern-data-architecture-accelerator.git","type":"git"},"description":"MDAA Bedrock Knowledge Base L3 Construct","maintainers":[{"name":"mdaa-dev-team","email":"mdaa-dev-team@amazon.com"}],"readme":"# Bedrock Knowledge Base L3 Construct\n\nThis construct provides a high-level abstraction for creating Amazon Bedrock Knowledge Bases with vector storage and data sources.\n\n## Features\n\n- **Knowledge Base Creation**: Creates Bedrock knowledge bases with vector configurations\n- **Vector Store Management**: Automatic Aurora PostgreSQL vector database setup\n- **S3 Data Sources**: Support for multiple S3 data sources with ingestion configurations\n- **Vector Ingestion**: Advanced parsing and chunking strategies\n- **Auto-Sync**: Optional Lambda-based automatic synchronization with S3 changes\n- **IAM Management**: Automatic creation of required IAM policies and roles\n- **Logging**: CloudWatch log group setup with delivery configuration\n\n## Usage\n\n```typescript\nimport { BedrockKnowledgeBaseL3Construct } from '@aws-mdaa/bedrock-knowledge-base-l3-construct';\n\nconst knowledgeBase = new BedrockKnowledgeBaseL3Construct(this, 'MyKB', {\n  kbName: 'my-knowledge-base',\n  kbConfig: {\n    role: kbExecutionRole,\n    vectorStore: 'my-vector-store',\n    embeddingModel: 'amazon.titan-embed-text-v2:0',\n    s3DataSources: {\n      documents: {\n        bucketName: 'my-docs-bucket',\n        prefix: 'documents/',\n        enableMultiSync: true\n      }\n    }\n  },\n  vectorStoreConfig: {\n    vpcId: 'vpc-12345',\n    subnetIds: ['subnet-1', 'subnet-2']\n  },\n  kmsKey: myKmsKey,\n  roleHelper: roleHelper,\n  naming: naming\n});\n```\n\n## Configuration Options\n\n### Knowledge Base Properties\n- `role`: Execution role for the knowledge base (required)\n- `vectorStore`: Reference to vector store configuration (required)\n- `embeddingModel`: Embedding model ID or ARN (required)\n- `s3DataSources`: Map of S3 data source configurations\n- `vectorFieldSize`: Optional vector field size override\n- `supplementalBucketName`: Optional supplemental storage bucket\n\n### Vector Store Properties\n- `vpcId`: VPC where the vector store will be deployed (required)\n- `subnetIds`: Subnet IDs for the vector store (required)\n- `port`: Optional database port (default: 5432)\n- `engineVersion`: Optional Aurora PostgreSQL version\n- `minCapacity`: Optional minimum Aurora Capacity Units\n- `maxCapacity`: Optional maximum Aurora Capacity Units\n\n### S3 Data Source Options\n- `bucketName`: S3 bucket name (required)\n- `prefix`: Optional S3 prefix filter\n- `enableSync`: Enable automatic sync on S3 changes limiting only one file at a time\n- `enableMultiSync`: Enable automatic sync on S3 bucket changes processing multiple file changes at the same time\n- `vectorIngestionConfiguration`: Advanced parsing and chunking options\n\n### Vector Ingestion Configuration\n- **Parsing Strategies**:\n  - `BEDROCK_DATA_AUTOMATION`: Automated multimodal parsing\n  - `BEDROCK_FOUNDATION_MODEL`: Custom foundation model parsing\n- **Chunking Strategies**:\n  - `FIXED_SIZE`: Fixed token-based chunking\n  - `HIERARCHICAL`: Parent-child chunking\n  - `SEMANTIC`: Meaning-based chunking\n  - `NONE`: No chunking\n\n## IAM Permissions\n\nThe construct automatically creates IAM policies with permissions for:\n- Embedding model invocation\n- Vector database access\n- S3 data source access\n- KMS key usage\n- Data source synchronization\n- CloudWatch logging\n\n## Dependencies\n\n- `@aws-mdaa/cloudwatch-constructs`\n- `@aws-mdaa/dataops-lambda-l3-construct`\n- `@aws-mdaa/ec2-constructs`\n- `@aws-mdaa/iam-constructs`\n- `@aws-mdaa/iam-role-helper`\n- `@aws-mdaa/kms-constructs`\n- `@aws-mdaa/l3-construct`\n- `@aws-mdaa/rds-constructs`\n- `@aws-mdaa/construct`\n- `aws-cdk-lib`\n- `constructs`","readmeFilename":"README.md"}