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package io.github.cdklabs.generative_ai_cdk_constructs.bedrock;
/**
* (experimental) Properties for a knowledge base.
*/
@javax.annotation.Generated(value = "jsii-pacmak/1.103.1 (build bef2dea)", date = "2024-09-23T18:35:37.402Z")
@software.amazon.jsii.Jsii(module = io.github.cdklabs.generative_ai_cdk_constructs.$Module.class, fqn = "@cdklabs/generative-ai-cdk-constructs.bedrock.KnowledgeBaseProps")
@software.amazon.jsii.Jsii.Proxy(KnowledgeBaseProps.Jsii$Proxy.class)
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public interface KnowledgeBaseProps extends software.amazon.jsii.JsiiSerializable {
/**
* (experimental) The embeddings model for the knowledge base.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@org.jetbrains.annotations.NotNull io.github.cdklabs.generative_ai_cdk_constructs.bedrock.BedrockFoundationModel getEmbeddingsModel();
/**
* (experimental) The description of the knowledge base.
*
* Default: - No description provided.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.lang.String getDescription() {
return null;
}
/**
* (experimental) Existing IAM role with a policy statement granting permission to invoke the specific embeddings model.
*
* Any entity (e.g., an AWS service or application) that assumes
* this role will be able to invoke or use the
* specified embeddings model within the Bedrock service.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable software.amazon.awscdk.services.iam.Role getExistingRole() {
return null;
}
/**
* (experimental) The name of the vector index.
*
* If vectorStore is not of type VectorCollection,
* do not include this property as it will throw error.
*
* Default: - 'bedrock-knowledge-base-default-index'
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.lang.String getIndexName() {
return null;
}
/**
* (experimental) A narrative description of the knowledge base.
*
* A Bedrock Agent can use this instruction to determine if it should
* query this Knowledge Base.
*
* Default: - No description provided.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.lang.String getInstruction() {
return null;
}
/**
* (experimental) Specifies whether to use the knowledge base or not when sending an InvokeAgent request.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.lang.String getKnowledgeBaseState() {
return null;
}
/**
* (experimental) The name of the knowledge base.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.lang.String getName() {
return null;
}
/**
* (experimental) OPTIONAL: Tag (KEY-VALUE) bedrock agent resource.
*
* Default: - false
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.util.Map getTags() {
return null;
}
/**
* (experimental) The name of the field in the vector index.
*
* If vectorStore is not of type VectorCollection,
* do not include this property as it will throw error.
*
* Default: - 'bedrock-knowledge-base-default-vector'
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.lang.String getVectorField() {
return null;
}
/**
* (experimental) The vector index for the OpenSearch Serverless backed knowledge base.
*
* If vectorStore is not of type VectorCollection, do not include
* this property as it will throw error.
*
* Default: - A new vector index is created on the Vector Collection
* if vector store is of `VectorCollection` type.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable io.github.cdklabs.generative_ai_cdk_constructs.opensearch_vectorindex.VectorIndex getVectorIndex() {
return null;
}
/**
* (experimental) The vector store for the knowledge base.
*
* Must be either of
* type VectorCollection, RedisEnterpriseVectorStore,
* PineconeVectorStore, AmazonAuroraVectorStore or
* AmazonAuroraDefaultVectorStore.
*
* Default: - A new OpenSearch Serverless vector collection is created.
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
default @org.jetbrains.annotations.Nullable java.lang.Object getVectorStore() {
return null;
}
/**
* @return a {@link Builder} of {@link KnowledgeBaseProps}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
static Builder builder() {
return new Builder();
}
/**
* A builder for {@link KnowledgeBaseProps}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public static final class Builder implements software.amazon.jsii.Builder {
io.github.cdklabs.generative_ai_cdk_constructs.bedrock.BedrockFoundationModel embeddingsModel;
java.lang.String description;
software.amazon.awscdk.services.iam.Role existingRole;
java.lang.String indexName;
java.lang.String instruction;
java.lang.String knowledgeBaseState;
java.lang.String name;
java.util.Map tags;
java.lang.String vectorField;
io.github.cdklabs.generative_ai_cdk_constructs.opensearch_vectorindex.VectorIndex vectorIndex;
java.lang.Object vectorStore;
/**
* Sets the value of {@link KnowledgeBaseProps#getEmbeddingsModel}
* @param embeddingsModel The embeddings model for the knowledge base. This parameter is required.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder embeddingsModel(io.github.cdklabs.generative_ai_cdk_constructs.bedrock.BedrockFoundationModel embeddingsModel) {
this.embeddingsModel = embeddingsModel;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getDescription}
* @param description The description of the knowledge base.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder description(java.lang.String description) {
this.description = description;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getExistingRole}
* @param existingRole Existing IAM role with a policy statement granting permission to invoke the specific embeddings model.
* Any entity (e.g., an AWS service or application) that assumes
* this role will be able to invoke or use the
* specified embeddings model within the Bedrock service.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder existingRole(software.amazon.awscdk.services.iam.Role existingRole) {
this.existingRole = existingRole;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getIndexName}
* @param indexName The name of the vector index.
* If vectorStore is not of type VectorCollection,
* do not include this property as it will throw error.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder indexName(java.lang.String indexName) {
this.indexName = indexName;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getInstruction}
* @param instruction A narrative description of the knowledge base.
* A Bedrock Agent can use this instruction to determine if it should
* query this Knowledge Base.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder instruction(java.lang.String instruction) {
this.instruction = instruction;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getKnowledgeBaseState}
* @param knowledgeBaseState Specifies whether to use the knowledge base or not when sending an InvokeAgent request.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder knowledgeBaseState(java.lang.String knowledgeBaseState) {
this.knowledgeBaseState = knowledgeBaseState;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getName}
* @param name The name of the knowledge base.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder name(java.lang.String name) {
this.name = name;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getTags}
* @param tags OPTIONAL: Tag (KEY-VALUE) bedrock agent resource.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder tags(java.util.Map tags) {
this.tags = tags;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getVectorField}
* @param vectorField The name of the field in the vector index.
* If vectorStore is not of type VectorCollection,
* do not include this property as it will throw error.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder vectorField(java.lang.String vectorField) {
this.vectorField = vectorField;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getVectorIndex}
* @param vectorIndex The vector index for the OpenSearch Serverless backed knowledge base.
* If vectorStore is not of type VectorCollection, do not include
* this property as it will throw error.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder vectorIndex(io.github.cdklabs.generative_ai_cdk_constructs.opensearch_vectorindex.VectorIndex vectorIndex) {
this.vectorIndex = vectorIndex;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getVectorStore}
* @param vectorStore The vector store for the knowledge base.
* Must be either of
* type VectorCollection, RedisEnterpriseVectorStore,
* PineconeVectorStore, AmazonAuroraVectorStore or
* AmazonAuroraDefaultVectorStore.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder vectorStore(io.github.cdklabs.generative_ai_cdk_constructs.amazonaurora.AmazonAuroraDefaultVectorStore vectorStore) {
this.vectorStore = vectorStore;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getVectorStore}
* @param vectorStore The vector store for the knowledge base.
* Must be either of
* type VectorCollection, RedisEnterpriseVectorStore,
* PineconeVectorStore, AmazonAuroraVectorStore or
* AmazonAuroraDefaultVectorStore.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder vectorStore(io.github.cdklabs.generative_ai_cdk_constructs.amazonaurora.AmazonAuroraVectorStore vectorStore) {
this.vectorStore = vectorStore;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getVectorStore}
* @param vectorStore The vector store for the knowledge base.
* Must be either of
* type VectorCollection, RedisEnterpriseVectorStore,
* PineconeVectorStore, AmazonAuroraVectorStore or
* AmazonAuroraDefaultVectorStore.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder vectorStore(io.github.cdklabs.generative_ai_cdk_constructs.opensearchserverless.VectorCollection vectorStore) {
this.vectorStore = vectorStore;
return this;
}
/**
* Sets the value of {@link KnowledgeBaseProps#getVectorStore}
* @param vectorStore The vector store for the knowledge base.
* Must be either of
* type VectorCollection, RedisEnterpriseVectorStore,
* PineconeVectorStore, AmazonAuroraVectorStore or
* AmazonAuroraDefaultVectorStore.
* @return {@code this}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
public Builder vectorStore(io.github.cdklabs.generative_ai_cdk_constructs.pinecone.PineconeVectorStore vectorStore) {
this.vectorStore = vectorStore;
return this;
}
/**
* Builds the configured instance.
* @return a new instance of {@link KnowledgeBaseProps}
* @throws NullPointerException if any required attribute was not provided
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@Override
public KnowledgeBaseProps build() {
return new Jsii$Proxy(this);
}
}
/**
* An implementation for {@link KnowledgeBaseProps}
*/
@software.amazon.jsii.Stability(software.amazon.jsii.Stability.Level.Experimental)
@software.amazon.jsii.Internal
final class Jsii$Proxy extends software.amazon.jsii.JsiiObject implements KnowledgeBaseProps {
private final io.github.cdklabs.generative_ai_cdk_constructs.bedrock.BedrockFoundationModel embeddingsModel;
private final java.lang.String description;
private final software.amazon.awscdk.services.iam.Role existingRole;
private final java.lang.String indexName;
private final java.lang.String instruction;
private final java.lang.String knowledgeBaseState;
private final java.lang.String name;
private final java.util.Map tags;
private final java.lang.String vectorField;
private final io.github.cdklabs.generative_ai_cdk_constructs.opensearch_vectorindex.VectorIndex vectorIndex;
private final java.lang.Object vectorStore;
/**
* Constructor that initializes the object based on values retrieved from the JsiiObject.
* @param objRef Reference to the JSII managed object.
*/
protected Jsii$Proxy(final software.amazon.jsii.JsiiObjectRef objRef) {
super(objRef);
this.embeddingsModel = software.amazon.jsii.Kernel.get(this, "embeddingsModel", software.amazon.jsii.NativeType.forClass(io.github.cdklabs.generative_ai_cdk_constructs.bedrock.BedrockFoundationModel.class));
this.description = software.amazon.jsii.Kernel.get(this, "description", software.amazon.jsii.NativeType.forClass(java.lang.String.class));
this.existingRole = software.amazon.jsii.Kernel.get(this, "existingRole", software.amazon.jsii.NativeType.forClass(software.amazon.awscdk.services.iam.Role.class));
this.indexName = software.amazon.jsii.Kernel.get(this, "indexName", software.amazon.jsii.NativeType.forClass(java.lang.String.class));
this.instruction = software.amazon.jsii.Kernel.get(this, "instruction", software.amazon.jsii.NativeType.forClass(java.lang.String.class));
this.knowledgeBaseState = software.amazon.jsii.Kernel.get(this, "knowledgeBaseState", software.amazon.jsii.NativeType.forClass(java.lang.String.class));
this.name = software.amazon.jsii.Kernel.get(this, "name", software.amazon.jsii.NativeType.forClass(java.lang.String.class));
this.tags = software.amazon.jsii.Kernel.get(this, "tags", software.amazon.jsii.NativeType.mapOf(software.amazon.jsii.NativeType.forClass(java.lang.String.class)));
this.vectorField = software.amazon.jsii.Kernel.get(this, "vectorField", software.amazon.jsii.NativeType.forClass(java.lang.String.class));
this.vectorIndex = software.amazon.jsii.Kernel.get(this, "vectorIndex", software.amazon.jsii.NativeType.forClass(io.github.cdklabs.generative_ai_cdk_constructs.opensearch_vectorindex.VectorIndex.class));
this.vectorStore = software.amazon.jsii.Kernel.get(this, "vectorStore", software.amazon.jsii.NativeType.forClass(java.lang.Object.class));
}
/**
* Constructor that initializes the object based on literal property values passed by the {@link Builder}.
*/
protected Jsii$Proxy(final Builder builder) {
super(software.amazon.jsii.JsiiObject.InitializationMode.JSII);
this.embeddingsModel = java.util.Objects.requireNonNull(builder.embeddingsModel, "embeddingsModel is required");
this.description = builder.description;
this.existingRole = builder.existingRole;
this.indexName = builder.indexName;
this.instruction = builder.instruction;
this.knowledgeBaseState = builder.knowledgeBaseState;
this.name = builder.name;
this.tags = builder.tags;
this.vectorField = builder.vectorField;
this.vectorIndex = builder.vectorIndex;
this.vectorStore = builder.vectorStore;
}
@Override
public final io.github.cdklabs.generative_ai_cdk_constructs.bedrock.BedrockFoundationModel getEmbeddingsModel() {
return this.embeddingsModel;
}
@Override
public final java.lang.String getDescription() {
return this.description;
}
@Override
public final software.amazon.awscdk.services.iam.Role getExistingRole() {
return this.existingRole;
}
@Override
public final java.lang.String getIndexName() {
return this.indexName;
}
@Override
public final java.lang.String getInstruction() {
return this.instruction;
}
@Override
public final java.lang.String getKnowledgeBaseState() {
return this.knowledgeBaseState;
}
@Override
public final java.lang.String getName() {
return this.name;
}
@Override
public final java.util.Map getTags() {
return this.tags;
}
@Override
public final java.lang.String getVectorField() {
return this.vectorField;
}
@Override
public final io.github.cdklabs.generative_ai_cdk_constructs.opensearch_vectorindex.VectorIndex getVectorIndex() {
return this.vectorIndex;
}
@Override
public final java.lang.Object getVectorStore() {
return this.vectorStore;
}
@Override
@software.amazon.jsii.Internal
public com.fasterxml.jackson.databind.JsonNode $jsii$toJson() {
final com.fasterxml.jackson.databind.ObjectMapper om = software.amazon.jsii.JsiiObjectMapper.INSTANCE;
final com.fasterxml.jackson.databind.node.ObjectNode data = com.fasterxml.jackson.databind.node.JsonNodeFactory.instance.objectNode();
data.set("embeddingsModel", om.valueToTree(this.getEmbeddingsModel()));
if (this.getDescription() != null) {
data.set("description", om.valueToTree(this.getDescription()));
}
if (this.getExistingRole() != null) {
data.set("existingRole", om.valueToTree(this.getExistingRole()));
}
if (this.getIndexName() != null) {
data.set("indexName", om.valueToTree(this.getIndexName()));
}
if (this.getInstruction() != null) {
data.set("instruction", om.valueToTree(this.getInstruction()));
}
if (this.getKnowledgeBaseState() != null) {
data.set("knowledgeBaseState", om.valueToTree(this.getKnowledgeBaseState()));
}
if (this.getName() != null) {
data.set("name", om.valueToTree(this.getName()));
}
if (this.getTags() != null) {
data.set("tags", om.valueToTree(this.getTags()));
}
if (this.getVectorField() != null) {
data.set("vectorField", om.valueToTree(this.getVectorField()));
}
if (this.getVectorIndex() != null) {
data.set("vectorIndex", om.valueToTree(this.getVectorIndex()));
}
if (this.getVectorStore() != null) {
data.set("vectorStore", om.valueToTree(this.getVectorStore()));
}
final com.fasterxml.jackson.databind.node.ObjectNode struct = com.fasterxml.jackson.databind.node.JsonNodeFactory.instance.objectNode();
struct.set("fqn", om.valueToTree("@cdklabs/generative-ai-cdk-constructs.bedrock.KnowledgeBaseProps"));
struct.set("data", data);
final com.fasterxml.jackson.databind.node.ObjectNode obj = com.fasterxml.jackson.databind.node.JsonNodeFactory.instance.objectNode();
obj.set("$jsii.struct", struct);
return obj;
}
@Override
public final boolean equals(final Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
KnowledgeBaseProps.Jsii$Proxy that = (KnowledgeBaseProps.Jsii$Proxy) o;
if (!embeddingsModel.equals(that.embeddingsModel)) return false;
if (this.description != null ? !this.description.equals(that.description) : that.description != null) return false;
if (this.existingRole != null ? !this.existingRole.equals(that.existingRole) : that.existingRole != null) return false;
if (this.indexName != null ? !this.indexName.equals(that.indexName) : that.indexName != null) return false;
if (this.instruction != null ? !this.instruction.equals(that.instruction) : that.instruction != null) return false;
if (this.knowledgeBaseState != null ? !this.knowledgeBaseState.equals(that.knowledgeBaseState) : that.knowledgeBaseState != null) return false;
if (this.name != null ? !this.name.equals(that.name) : that.name != null) return false;
if (this.tags != null ? !this.tags.equals(that.tags) : that.tags != null) return false;
if (this.vectorField != null ? !this.vectorField.equals(that.vectorField) : that.vectorField != null) return false;
if (this.vectorIndex != null ? !this.vectorIndex.equals(that.vectorIndex) : that.vectorIndex != null) return false;
return this.vectorStore != null ? this.vectorStore.equals(that.vectorStore) : that.vectorStore == null;
}
@Override
public final int hashCode() {
int result = this.embeddingsModel.hashCode();
result = 31 * result + (this.description != null ? this.description.hashCode() : 0);
result = 31 * result + (this.existingRole != null ? this.existingRole.hashCode() : 0);
result = 31 * result + (this.indexName != null ? this.indexName.hashCode() : 0);
result = 31 * result + (this.instruction != null ? this.instruction.hashCode() : 0);
result = 31 * result + (this.knowledgeBaseState != null ? this.knowledgeBaseState.hashCode() : 0);
result = 31 * result + (this.name != null ? this.name.hashCode() : 0);
result = 31 * result + (this.tags != null ? this.tags.hashCode() : 0);
result = 31 * result + (this.vectorField != null ? this.vectorField.hashCode() : 0);
result = 31 * result + (this.vectorIndex != null ? this.vectorIndex.hashCode() : 0);
result = 31 * result + (this.vectorStore != null ? this.vectorStore.hashCode() : 0);
return result;
}
}
}