chore(aurora): aurora bug fix and readme misc updates (#981)

* chore(misc): aurora bug fix and readme misc updates

---------

Signed-off-by: Alain Krok <[email protected]>

Author: krokoko

README.md

@@ -168,6 +168,7 @@ The official [samples repository](https://github.com/aws-samples/generative-ai-c
 | [Automating tasks using Amazon Bedrock Agents and AI](https://blog.serverlessadvocate.com/automating-tasks-using-amazon-bedrock-agents-and-ai-4b6fb8856589) | Blog post + Code sample | Blog post and associated code sample demonstrating how to deploy an Amazon Bedrock Agent and a Knowledge Base through a hotel and spa use case. |
 | [Agents for Amazon Bedrock - Powertools for AWS Lambda (Python)](https://docs.powertools.aws.dev/lambda/python/latest/core/event_handler/bedrock_agents/#using-aws-cloud-developer-kit-cdk) | Code sample | Create Agents for Amazon Bedrock using event handlers and auto generation of OpenAPI schemas. |
 | [Text to SQL Bedrock Agent](https://github.com/aws-samples/amazon-bedrock-samples/tree/main/agents-for-bedrock/use-case-examples/text-2-sql-agent-cdk-enhanced) | Code sample | Harnessing the power of natural language processing, the "Text to SQL Bedrock Agent" facilitates the automatic transformation of natural language questions into executable SQL queries. |
+| [Dynamic Text-to-SQL for Enterprise Workloads with Amazon Bedrock Agent](https://github.com/aws-samples/sample-Dynamic-Text-to-SQL-with-Amazon-Bedrock-Agent) | Code sample | Elevate your data analysis with an end-to-end agentic Text-to-SQL solution, built on AWS for enterprise-scale adaptability and resilience. Ideal for complex scenarios like fraud detection in financial services. |
 
 ## Contributors
 

apidocs/namespaces/amazonaurora/interfaces/AmazonAuroraVectorStoreProps.md

@@ -14,6 +14,14 @@ Properties for configuring an Amazon Aurora Vector Store.
 
 ## Properties
 
+### clusterId?
+
+> `readonly` `optional` **clusterId**: `string`
+
+Cluster identifier.
+
+***
+
 ### databaseName?
 
 > `readonly` `optional` **databaseName**: `string`

apidocs/namespaces/bedrock/classes/BedrockFoundationModel.md

@@ -95,6 +95,28 @@ The ARN of the Bedrock invokable abstraction.
 
 ***
 
+### AI21\_JAMBA\_1\_5\_LARGE\_V1
+
+> `readonly` `static` **AI21\_JAMBA\_1\_5\_LARGE\_V1**: [`BedrockFoundationModel`](BedrockFoundationModel.md)
+
+*************************************************************************
+                           AI21
+*************************************************************************
+
+***
+
+### AI21\_JAMBA\_1\_5\_MINI\_V1
+
+> `readonly` `static` **AI21\_JAMBA\_1\_5\_MINI\_V1**: [`BedrockFoundationModel`](BedrockFoundationModel.md)
+
+***
+
+### AI21\_JAMBA\_INSTRUCT\_V1
+
+> `readonly` `static` **AI21\_JAMBA\_INSTRUCT\_V1**: [`BedrockFoundationModel`](BedrockFoundationModel.md)
+
+***
+
 ### AMAZON\_NOVA\_LITE\_V1
 
 > `readonly` `static` **AMAZON\_NOVA\_LITE\_V1**: [`BedrockFoundationModel`](BedrockFoundationModel.md)
@@ -243,6 +265,12 @@ The ARN of the Bedrock invokable abstraction.
 
 ***
 
+### META\_LLAMA\_3\_3\_70B\_INSTRUCT\_V1
+
+> `readonly` `static` **META\_LLAMA\_3\_3\_70B\_INSTRUCT\_V1**: [`BedrockFoundationModel`](BedrockFoundationModel.md)
+
+***
+
 ### TITAN\_EMBED\_TEXT\_V1
 
 > `readonly` `static` **TITAN\_EMBED\_TEXT\_V1**: [`BedrockFoundationModel`](BedrockFoundationModel.md)

apidocs/namespaces/bedrock/interfaces/BedrockFoundationModelProps.md

@@ -8,6 +8,35 @@
 
 ## Properties
 
+### legacy?
+
+> `readonly` `optional` **legacy**: `boolean`
+
+https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle.html
+A version is marked Legacy when there is a more recent version which provides superior performance. Amazon Bedrock sets an EOL date for Legacy versions.
+
+#### Default
+
+```ts
+- false
+```
+
+***
+
+### optimizedForAgents?
+
+> `readonly` `optional` **optimizedForAgents**: `boolean`
+
+Currently, some of the offered models are optimized with prompts/parsers fine-tuned for integrating with the agents architecture.
+
+#### Default
+
+```ts
+- false
+```
+
+***
+
 ### supportedVectorType?
 
 > `readonly` `optional` **supportedVectorType**: [`VectorType`](../enumerations/VectorType.md)[]

lambda/amazon-aurora-pgvector-custom-resources/custom_resources/amazon_aurora_pgvector.py

@@ -85,20 +85,18 @@ def execute_sql_commands(
 ):
     try:
         with conn.cursor() as cur:
-
             cur.execute("CREATE EXTENSION IF NOT EXISTS vector;")
-            cur.execute("CREATE SCHEMA IF NOT EXISTS %s;", (schema_name,))
+            cur.execute(f"CREATE SCHEMA IF NOT EXISTS {schema_name};")
 
-            cur.execute("CREATE ROLE bedrock_user WITH PASSWORD %s LOGIN;", (password,))
-            cur.execute("GRANT ALL ON SCHEMA %s TO bedrock_user;", (schema_name,))
+            cur.execute(f"CREATE ROLE bedrock_user WITH PASSWORD '{password}' LOGIN;")
+            cur.execute(f"GRANT ALL ON SCHEMA {schema_name} TO bedrock_user;")
 
             cur.execute(
                 f"CREATE TABLE {schema_name}.{table_name} ("
                 f"{pk_field} uuid PRIMARY KEY, "
-                f"{vector_field} vector(%s), "
+                f"{vector_field} vector({vector_dimensions}), "
                 f"{text_field} text, "
-                f"{metadata_field} json);",
-                (vector_dimensions,),
+                f"{metadata_field} json);"
             )
 
             cur.execute(

src/cdk-lib/amazonaurora/README.md

@@ -95,7 +95,7 @@ const auroraDb = amazonaurora.AmazonAuroraVectorStore.fromExistingAuroraVectorSt
   ),
 });
 
-const kb = new bedrock.KnowledgeBase(this, "KnowledgeBase", {
+const kb = new bedrock.VectorKnowledgeBase(this, "KnowledgeBase", {
   embeddingsModel: foundation_models.BedrockFoundationModel.COHERE_EMBED_ENGLISH_V3,
   vectorStore: auroraDb,
   instruction:
@@ -158,7 +158,7 @@ aurora_db = amazonaurora.AmazonAuroraVectorStore.from_existing_aurora_vector_sto
     )
 )
 
-kb = bedrock.KnowledgeBase(self, 'KnowledgeBase',
+kb = bedrock.VectorKnowledgeBase(self, 'KnowledgeBase',
             embeddings_model= foundation_models.BedrockFoundationModel.TITAN_EMBED_TEXT_V1,
             vector_store=aurora_db,
             instruction=  'Use this knowledge base to answer questions about books. ' +

src/cdk-lib/amazonaurora/aurora-vector-store.ts

@@ -104,6 +104,11 @@ export interface AmazonAuroraVectorStoreProps extends BaseAuroraVectorStoreProps
    * User's VPC in which they want to deploy Aurora Database.
    */
   readonly vpc?: ec2.IVpc;
+
+  /**
+   * Cluster identifier.
+   */
+  readonly clusterId?: string;
 }
 
 /**
@@ -482,6 +487,7 @@ export class AmazonAuroraVectorStore extends BaseAmazonAuroraVectorStore {
     const databaseClusterResources = this.createDatabaseCluster(
       props.postgreSQLVersion ?? SupportedPostgreSQLVersions.AURORA_POSTGRESQL_V15_5,
       props.vpc,
+      props.clusterId,
     );
     const auroraPgCRPolicy = this.createAuroraPgCRPolicy(databaseClusterResources.clusterIdentifier);
     const lambdaSecurityGroup = this.createLambdaSecurityGroup(databaseClusterResources.vpc);
@@ -504,6 +510,7 @@ export class AmazonAuroraVectorStore extends BaseAmazonAuroraVectorStore {
   private createDatabaseCluster(
     postgreSQLVersion: SupportedPostgreSQLVersions,
     existingVpc: ec2.IVpc | undefined,
+    clusterIdentifier: string | undefined,
   ): DatabaseClusterResources {
     const vpc = buildVpc(this, {
       existingVpc: existingVpc,
@@ -524,7 +531,7 @@ export class AmazonAuroraVectorStore extends BaseAmazonAuroraVectorStore {
         version: postgreSQLVersion,
       }),
       credentials: rds.Credentials.fromGeneratedSecret('postgres'),
-      clusterIdentifier: `aurora-serverless-vector-cluster-${cdk.Stack.of(this).account}`,
+      clusterIdentifier: clusterIdentifier ?? generatePhysicalNameV2(this, 'aurora-serverless', { maxLength: 63, lower: true, separator: '-' }),
       defaultDatabaseName: this.databaseName,
       vpc,
       vpcSubnets: { subnetType: ec2.SubnetType.PRIVATE_ISOLATED },

src/cdk-lib/bedrock/README.md

@@ -148,7 +148,7 @@ const auroraDb = new amazonaurora.AmazonAuroraVectorStore(stack, 'AuroraDefaultV
 
 const kb = new bedrock.VectorKnowledgeBase(this, 'KnowledgeBase', {
   vectorStore: auroraDb,
-  embeddingsModelVectorDimension: embeddingsModelVectorDimension,
+  embeddingsModel: foundation_models.BedrockFoundationModel.TITAN_EMBED_TEXT_V1,
   instruction: 'Use this knowledge base to answer questions about books. ' + 'It contains the full text of novels.',
 });
 
@@ -185,19 +185,19 @@ aurora_db = amazonaurora.AmazonAuroraVectorStore(self, 'AuroraDefaultVectorStore
 )
 
 kb = bedrock.VectorKnowledgeBase(self, 'KnowledgeBase',
-            vector_store= aurora_db,
-            embeddings_model_vector_dimension=embeddings_model_vector_dimension,
-            instruction=  'Use this knowledge base to answer questions about books. ' +
-    'It contains the full text of novels.'
-        )
+  vector_store= aurora_db,
+  embeddings_model= foundation_models.BedrockFoundationModel.TITAN_EMBED_TEXT_V1,
+  instruction=  'Use this knowledge base to answer questions about books. ' +
+'It contains the full text of novels.'
+)
 
 docBucket = s3.Bucket(self, 'DockBucket')
 
 bedrock.S3DataSource(self, 'DataSource',
-    bucket= docBucket,
-    knowledge_base=kb,
-    data_source_name='books',
-    chunking_strategy= bedrock.ChunkingStrategy.FIXED_SIZE,
+  bucket= docBucket,
+  knowledge_base=kb,
+  data_source_name='books',
+  chunking_strategy= bedrock.ChunkingStrategy.FIXED_SIZE,
 )
 
 ```

src/cdk-lib/bedrock/models.ts

@@ -57,6 +57,19 @@ export interface BedrockFoundationModelProps {
    * @default - false
    */
   readonly supportsAgents?: boolean;
+  /**
+   * Currently, some of the offered models are optimized with prompts/parsers fine-tuned for integrating with the agents architecture.
+   *
+   * @default - false
+   */
+  readonly optimizedForAgents?: boolean;
+  /**
+   * https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle.html
+   * A version is marked Legacy when there is a more recent version which provides superior performance. Amazon Bedrock sets an EOL date for Legacy versions.
+   *
+   * @default - false
+   */
+  readonly legacy?: boolean;
   /**
    * Bedrock Knowledge Base can use this model.
    *
@@ -86,6 +99,20 @@ export interface BedrockFoundationModelProps {
  * can instantiate a `BedrockFoundationModel` object, e.g: `new BedrockFoundationModel('my-model')`.
  */
 export class BedrockFoundationModel implements IInvokable {
+  /****************************************************************************
+   *                            AI21
+   ***************************************************************************/
+  public static readonly AI21_JAMBA_1_5_LARGE_V1 = new BedrockFoundationModel('ai21.jamba-1-5-large-v1:0', {
+    supportsAgents: true,
+  });
+
+  public static readonly AI21_JAMBA_1_5_MINI_V1 = new BedrockFoundationModel('ai21.jamba-1-5-mini-v1:0', {
+    supportsAgents: true,
+  });
+
+  public static readonly AI21_JAMBA_INSTRUCT_V1 = new BedrockFoundationModel('ai21.jamba-instruct-v1:0', {
+    supportsAgents: true,
+  });
   /****************************************************************************
    *                            AMAZON
    ***************************************************************************/
@@ -100,16 +127,19 @@ export class BedrockFoundationModel implements IInvokable {
   public static readonly AMAZON_NOVA_MICRO_V1 = new BedrockFoundationModel('amazon.nova-micro-v1:0', {
     supportsAgents: true,
     supportsCrossRegion: true,
+    optimizedForAgents: true,
   });
 
   public static readonly AMAZON_NOVA_LITE_V1 = new BedrockFoundationModel('amazon.nova-lite-v1:0', {
     supportsAgents: true,
     supportsCrossRegion: true,
+    optimizedForAgents: true,
   });
 
   public static readonly AMAZON_NOVA_PRO_V1 = new BedrockFoundationModel('amazon.nova-pro-v1:0', {
     supportsAgents: true,
     supportsCrossRegion: true,
+    optimizedForAgents: true,
   });
 
   public static readonly TITAN_EMBED_TEXT_V1 = new BedrockFoundationModel('amazon.titan-embed-text-v1', {
@@ -140,49 +170,56 @@ export class BedrockFoundationModel implements IInvokable {
    ***************************************************************************/
   public static readonly ANTHROPIC_CLAUDE_3_7_SONNET_V1_0 = new BedrockFoundationModel(
     'anthropic.claude-3-7-sonnet-20250219-v1:0',
-    { supportsAgents: true, supportsCrossRegion: true },
+
+    { supportsAgents: true, supportsCrossRegion: true, optimizedForAgents: false },
   );
 
   public static readonly ANTHROPIC_CLAUDE_3_5_SONNET_V2_0 = new BedrockFoundationModel(
     'anthropic.claude-3-5-sonnet-20241022-v2:0',
-    { supportsAgents: true, supportsCrossRegion: true },
+    { supportsAgents: true, supportsCrossRegion: true, optimizedForAgents: true },
   );
 
   public static readonly ANTHROPIC_CLAUDE_3_5_SONNET_V1_0 = new BedrockFoundationModel(
     'anthropic.claude-3-5-sonnet-20240620-v1:0',
-    { supportsAgents: true, supportsCrossRegion: true },
+    { supportsAgents: true, supportsCrossRegion: true, optimizedForAgents: true },
   );
 
   public static readonly ANTHROPIC_CLAUDE_3_5_HAIKU_V1_0 = new BedrockFoundationModel(
     'anthropic.claude-3-5-haiku-20241022-v1:0',
-    { supportsAgents: true, supportsCrossRegion: true },
+    { supportsAgents: true, supportsCrossRegion: true, optimizedForAgents: true },
   );
 
   public static readonly ANTHROPIC_CLAUDE_OPUS_V1_0 = new BedrockFoundationModel(
     'anthropic.claude-3-opus-20240229-v1:0',
-    { supportsAgents: true },
+    { supportsAgents: true, optimizedForAgents: true },
   );
 
   public static readonly ANTHROPIC_CLAUDE_SONNET_V1_0 = new BedrockFoundationModel(
     'anthropic.claude-3-sonnet-20240229-v1:0',
-    { supportsAgents: true, supportsCrossRegion: true },
+    { supportsAgents: true, supportsCrossRegion: true, legacy: true, optimizedForAgents: true },
   );
 
   public static readonly ANTHROPIC_CLAUDE_HAIKU_V1_0 = new BedrockFoundationModel(
     'anthropic.claude-3-haiku-20240307-v1:0',
-    { supportsAgents: true, supportsCrossRegion: true },
+    { supportsAgents: true, supportsCrossRegion: true, optimizedForAgents: true },
   );
 
   public static readonly ANTHROPIC_CLAUDE_V2_1 = new BedrockFoundationModel('anthropic.claude-v2:1', {
     supportsAgents: true,
+    legacy: true,
+    optimizedForAgents: true,
   });
 
   public static readonly ANTHROPIC_CLAUDE_V2 = new BedrockFoundationModel('anthropic.claude-v2', {
     supportsAgents: true,
+    legacy: true,
+    optimizedForAgents: true,
   });
 
   public static readonly ANTHROPIC_CLAUDE_INSTANT_V1_2 = new BedrockFoundationModel('anthropic.claude-instant-v1', {
     supportsAgents: true,
+    legacy: true,
+    optimizedForAgents: true,
   });
 
   /****************************************************************************
@@ -204,28 +241,38 @@ export class BedrockFoundationModel implements IInvokable {
    *                            META
    ***************************************************************************/
   public static readonly META_LLAMA_3_1_8B_INSTRUCT_V1 = new BedrockFoundationModel('meta.llama3-1-8b-instruct-v1:0', {
+    supportsAgents: true,
     supportsCrossRegion: true,
   });
 
   public static readonly META_LLAMA_3_1_70B_INSTRUCT_V1 = new BedrockFoundationModel(
     'meta.llama3-1-70b-instruct-v1:0',
     {
+      supportsAgents: true,
       supportsCrossRegion: true,
     },
   );
 
   public static readonly META_LLAMA_3_2_11B_INSTRUCT_V1 = new BedrockFoundationModel(
     'meta.llama3-2-11b-instruct-v1:0',
     {
+      supportsAgents: true,
       supportsCrossRegion: true,
     },
   );
 
   public static readonly META_LLAMA_3_2_3B_INSTRUCT_V1 = new BedrockFoundationModel('meta.llama3-2-3b-instruct-v1:0', {
+    supportsAgents: true,
     supportsCrossRegion: true,
   });
 
   public static readonly META_LLAMA_3_2_1B_INSTRUCT_V1 = new BedrockFoundationModel('meta.llama3-2-1b-instruct-v1:0', {
+    supportsAgents: true,
+    supportsCrossRegion: true,
+  });
+
+  public static readonly META_LLAMA_3_3_70B_INSTRUCT_V1 = new BedrockFoundationModel('meta.llama3-3-70b-instruct-v1:0', {
+    supportsAgents: true,
     supportsCrossRegion: true,
   });